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1 | 1 | # Copyright (c) 2012-2020 Jicamarca Radio Observatory |
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2 | 2 | # All rights reserved. |
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3 | 3 | # |
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4 | 4 | # Distributed under the terms of the BSD 3-clause license. |
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5 | 5 | """API to create signal chain projects |
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6 | 6 | |
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7 | 7 | The API is provide through class: Project |
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8 | 8 | """ |
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9 | 9 | |
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10 | 10 | import re |
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11 | 11 | import sys |
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12 | 12 | import ast |
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13 | 13 | import datetime |
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14 | 14 | import traceback |
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15 | 15 | import time |
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16 | 16 | import multiprocessing |
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17 | 17 | from multiprocessing import Process, Queue |
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18 | 18 | from threading import Thread |
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19 | 19 | from xml.etree.ElementTree import ElementTree, Element, SubElement |
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20 | 20 | |
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21 | 21 | from schainpy.admin import Alarm, SchainWarning |
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22 | 22 | from schainpy.model import * |
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23 | 23 | from schainpy.utils import log |
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24 | 24 | |
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25 | 25 | if 'darwin' in sys.platform and sys.version_info[0] == 3 and sys.version_info[1] > 7: |
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26 | 26 | multiprocessing.set_start_method('fork') |
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27 | 27 | |
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28 | 28 | class ConfBase(): |
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29 | 29 | |
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30 | 30 | def __init__(self): |
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31 | 31 | |
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32 | 32 | self.id = '0' |
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33 | 33 | self.name = None |
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34 | 34 | self.priority = None |
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35 | 35 | self.parameters = {} |
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36 | 36 | self.object = None |
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37 | 37 | self.operations = [] |
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38 | 38 | |
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39 | 39 | def getId(self): |
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40 | 40 | |
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41 | 41 | return self.id |
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42 | 42 | |
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43 | 43 | def getNewId(self): |
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44 | 44 | |
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45 | 45 | return int(self.id) * 10 + len(self.operations) + 1 |
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46 | 46 | |
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47 | 47 | def updateId(self, new_id): |
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48 | 48 | |
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49 | 49 | self.id = str(new_id) |
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50 | 50 | |
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51 | 51 | n = 1 |
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52 | 52 | for conf in self.operations: |
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53 | 53 | conf_id = str(int(new_id) * 10 + n) |
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54 | 54 | conf.updateId(conf_id) |
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55 | 55 | n += 1 |
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56 | 56 | |
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57 | 57 | def getKwargs(self): |
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58 | 58 | |
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59 | 59 | params = {} |
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60 | 60 | |
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61 | 61 | for key, value in self.parameters.items(): |
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62 | 62 | if value not in (None, '', ' '): |
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63 | 63 | params[key] = value |
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64 | 64 | |
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65 | 65 | return params |
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66 | 66 | |
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67 | 67 | def update(self, **kwargs): |
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68 | 68 | |
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69 | 69 | if 'format' not in kwargs: |
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70 | 70 | kwargs['format'] = None |
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71 | 71 | for key, value, fmt in kwargs.items(): |
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72 | 72 | self.addParameter(name=key, value=value, format=fmt) |
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73 | 73 | |
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74 | 74 | def addParameter(self, name, value, format=None): |
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75 | 75 | ''' |
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76 | 76 | ''' |
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77 | 77 | if format is not None: |
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78 | 78 | self.parameters[name] = eval(format)(value) |
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79 | 79 | elif isinstance(value, str) and re.search(r'(\d+/\d+/\d+)', value): |
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80 | 80 | self.parameters[name] = datetime.date(*[int(x) for x in value.split('/')]) |
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81 | 81 | elif isinstance(value, str) and re.search(r'(\d+:\d+:\d+)', value): |
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82 | 82 | self.parameters[name] = datetime.time(*[int(x) for x in value.split(':')]) |
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83 | 83 | else: |
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84 | 84 | try: |
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85 | 85 | self.parameters[name] = ast.literal_eval(value) |
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86 | 86 | except: |
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87 | 87 | if isinstance(value, str) and ',' in value: |
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88 | 88 | self.parameters[name] = value.split(',') |
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89 | 89 | else: |
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90 | 90 | self.parameters[name] = value |
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91 | 91 | |
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92 | 92 | def getParameters(self): |
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93 | 93 | |
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94 | 94 | params = {} |
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95 | 95 | for key, value in self.parameters.items(): |
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96 | 96 | s = type(value).__name__ |
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97 | 97 | if s == 'date': |
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98 | 98 | params[key] = value.strftime('%Y/%m/%d') |
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99 | 99 | elif s == 'time': |
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100 | 100 | params[key] = value.strftime('%H:%M:%S') |
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101 | 101 | else: |
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102 | 102 | params[key] = str(value) |
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103 | 103 | |
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104 | 104 | return params |
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105 | 105 | |
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106 | 106 | def makeXml(self, element): |
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107 | 107 | |
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108 | 108 | xml = SubElement(element, self.ELEMENTNAME) |
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109 | 109 | for label in self.xml_labels: |
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110 | 110 | xml.set(label, str(getattr(self, label))) |
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111 | 111 | |
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112 | 112 | for key, value in self.getParameters().items(): |
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113 | 113 | xml_param = SubElement(xml, 'Parameter') |
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114 | 114 | xml_param.set('name', key) |
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115 | 115 | xml_param.set('value', value) |
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116 | 116 | |
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117 | 117 | for conf in self.operations: |
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118 | 118 | conf.makeXml(xml) |
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119 | 119 | |
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120 | 120 | def __str__(self): |
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121 | 121 | |
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122 | 122 | if self.ELEMENTNAME == 'Operation': |
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123 | 123 | s = ' {}[id={}]\n'.format(self.name, self.id) |
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124 | 124 | else: |
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125 | 125 | s = '{}[id={}, inputId={}]\n'.format(self.name, self.id, self.inputId) |
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126 | 126 | |
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127 | 127 | for key, value in self.parameters.items(): |
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128 | 128 | if self.ELEMENTNAME == 'Operation': |
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129 | 129 | s += ' {}: {}\n'.format(key, value) |
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130 | 130 | else: |
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131 | 131 | s += ' {}: {}\n'.format(key, value) |
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132 | 132 | |
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133 | 133 | for conf in self.operations: |
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134 | 134 | s += str(conf) |
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135 | 135 | |
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136 | 136 | return s |
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137 | 137 | |
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138 | 138 | class OperationConf(ConfBase): |
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139 | 139 | |
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140 | 140 | ELEMENTNAME = 'Operation' |
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141 | 141 | xml_labels = ['id', 'name'] |
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142 | 142 | |
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143 | 143 | def setup(self, id, name, priority, project_id, err_queue): |
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144 | 144 | |
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145 | 145 | self.id = str(id) |
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146 | 146 | self.project_id = project_id |
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147 | 147 | self.name = name |
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148 | 148 | self.type = 'other' |
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149 | 149 | self.err_queue = err_queue |
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150 | 150 | |
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151 | 151 | def readXml(self, element, project_id, err_queue): |
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152 | 152 | |
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153 | 153 | self.id = element.get('id') |
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154 | 154 | self.name = element.get('name') |
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155 | 155 | self.type = 'other' |
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156 | 156 | self.project_id = str(project_id) |
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157 | 157 | self.err_queue = err_queue |
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158 | 158 | |
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159 | 159 | for elm in element.iter('Parameter'): |
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160 | 160 | self.addParameter(elm.get('name'), elm.get('value')) |
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161 | 161 | |
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162 | 162 | def createObject(self): |
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163 | 163 | |
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164 | 164 | className = eval(self.name) |
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165 | 165 | |
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166 | 166 | if 'Plot' in self.name or 'Writer' in self.name or 'Send' in self.name or 'print' in self.name: |
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167 | 167 | kwargs = self.getKwargs() |
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168 | 168 | opObj = className(self.id, self.id, self.project_id, self.err_queue, **kwargs) |
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169 | 169 | opObj.start() |
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170 | 170 | self.type = 'external' |
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171 | 171 | else: |
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172 | 172 | opObj = className() |
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173 | 173 | |
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174 | 174 | self.object = opObj |
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175 | 175 | return opObj |
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176 | 176 | |
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177 | 177 | class ProcUnitConf(ConfBase): |
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178 | 178 | |
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179 | 179 | ELEMENTNAME = 'ProcUnit' |
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180 | 180 | xml_labels = ['id', 'inputId', 'name'] |
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181 | 181 | |
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182 | 182 | def setup(self, project_id, id, name, datatype, inputId, err_queue): |
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183 | 183 | ''' |
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184 | 184 | ''' |
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185 | 185 | |
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186 | 186 | if datatype == None and name == None: |
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187 | 187 | raise ValueError('datatype or name should be defined') |
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188 | 188 | |
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189 | 189 | if name == None: |
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190 | 190 | if 'Proc' in datatype: |
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191 | 191 | name = datatype |
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192 | 192 | else: |
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193 | 193 | name = '%sProc' % (datatype) |
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194 | 194 | |
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195 | 195 | if datatype == None: |
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196 | 196 | datatype = name.replace('Proc', '') |
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197 | 197 | |
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198 | 198 | self.id = str(id) |
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199 | 199 | self.project_id = project_id |
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200 | 200 | self.name = name |
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201 | 201 | self.datatype = datatype |
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202 | 202 | self.inputId = inputId |
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203 | 203 | self.err_queue = err_queue |
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204 | 204 | self.operations = [] |
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205 | 205 | self.parameters = {} |
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206 | 206 | |
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207 | 207 | def removeOperation(self, id): |
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208 | 208 | |
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209 | 209 | i = [1 if x.id==id else 0 for x in self.operations] |
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210 | 210 | self.operations.pop(i.index(1)) |
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211 | 211 | |
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212 | 212 | def getOperation(self, id): |
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213 | 213 | |
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214 | 214 | for conf in self.operations: |
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215 | 215 | if conf.id == id: |
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216 | 216 | return conf |
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217 | 217 | |
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218 | 218 | def addOperation(self, name, optype='self'): |
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219 | 219 | ''' |
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220 | 220 | ''' |
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221 | 221 | |
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222 | 222 | id = self.getNewId() |
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223 | 223 | conf = OperationConf() |
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224 | 224 | conf.setup(id, name=name, priority='0', project_id=self.project_id, err_queue=self.err_queue) |
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225 | 225 | self.operations.append(conf) |
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226 | 226 | |
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227 | 227 | return conf |
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228 | 228 | |
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229 | 229 | def readXml(self, element, project_id, err_queue): |
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230 | 230 | |
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231 | 231 | self.id = element.get('id') |
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232 | 232 | self.name = element.get('name') |
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233 | 233 | self.inputId = None if element.get('inputId') == 'None' else element.get('inputId') |
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234 | 234 | self.datatype = element.get('datatype', self.name.replace(self.ELEMENTNAME.replace('Unit', ''), '')) |
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235 | 235 | self.project_id = str(project_id) |
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236 | 236 | self.err_queue = err_queue |
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237 | 237 | self.operations = [] |
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238 | 238 | self.parameters = {} |
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239 | 239 | |
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240 | 240 | for elm in element: |
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241 | 241 | if elm.tag == 'Parameter': |
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242 | 242 | self.addParameter(elm.get('name'), elm.get('value')) |
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243 | 243 | elif elm.tag == 'Operation': |
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244 | 244 | conf = OperationConf() |
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245 | 245 | conf.readXml(elm, project_id, err_queue) |
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246 | 246 | self.operations.append(conf) |
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247 | 247 | |
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248 | 248 | def createObjects(self): |
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249 | 249 | ''' |
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250 | 250 | Instancia de unidades de procesamiento. |
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251 | 251 | ''' |
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252 | 252 | |
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253 | 253 | className = eval(self.name) |
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254 | 254 | kwargs = self.getKwargs() |
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255 | 255 | procUnitObj = className() |
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256 | 256 | procUnitObj.name = self.name |
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257 | 257 | log.success('creating process...', self.name) |
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258 | 258 | |
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259 | 259 | for conf in self.operations: |
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260 | 260 | |
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261 | 261 | opObj = conf.createObject() |
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262 | 262 | |
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263 | 263 | log.success('adding operation: {}, type:{}'.format( |
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264 | 264 | conf.name, |
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265 | 265 | conf.type), self.name) |
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266 | 266 | |
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267 | 267 | procUnitObj.addOperation(conf, opObj) |
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268 | 268 | |
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269 | 269 | self.object = procUnitObj |
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270 | 270 | |
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271 | 271 | def run(self): |
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272 | 272 | ''' |
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273 | 273 | ''' |
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274 | 274 | |
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275 | 275 | return self.object.call(**self.getKwargs()) |
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276 | 276 | |
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277 | 277 | |
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278 | 278 | class ReadUnitConf(ProcUnitConf): |
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279 | 279 | |
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280 | 280 | ELEMENTNAME = 'ReadUnit' |
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281 | 281 | |
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282 | 282 | def __init__(self): |
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283 | 283 | |
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284 | 284 | self.id = None |
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285 | 285 | self.datatype = None |
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286 | 286 | self.name = None |
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287 | 287 | self.inputId = None |
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288 | 288 | self.operations = [] |
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289 | 289 | self.parameters = {} |
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290 | 290 | |
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291 | 291 | def setup(self, project_id, id, name, datatype, err_queue, path='', startDate='', endDate='', |
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292 | 292 | startTime='', endTime='', server=None, **kwargs): |
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293 | 293 | |
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294 | 294 | if datatype == None and name == None: |
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295 | 295 | raise ValueError('datatype or name should be defined') |
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296 | 296 | if name == None: |
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297 | 297 | if 'Reader' in datatype: |
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298 | 298 | name = datatype |
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299 | 299 | datatype = name.replace('Reader','') |
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300 | 300 | else: |
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301 | 301 | name = '{}Reader'.format(datatype) |
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302 | 302 | if datatype == None: |
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303 | 303 | if 'Reader' in name: |
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304 | 304 | datatype = name.replace('Reader','') |
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305 | 305 | else: |
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306 | 306 | datatype = name |
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307 | 307 | name = '{}Reader'.format(name) |
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308 | 308 | |
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309 | 309 | self.id = id |
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310 | 310 | self.project_id = project_id |
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311 | 311 | self.name = name |
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312 | 312 | self.datatype = datatype |
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313 | 313 | self.err_queue = err_queue |
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314 | 314 | |
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315 | 315 | self.addParameter(name='path', value=path, format='str') |
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316 | 316 | self.addParameter(name='startDate', value=startDate) |
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317 | 317 | self.addParameter(name='endDate', value=endDate) |
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318 | 318 | self.addParameter(name='startTime', value=startTime) |
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319 | 319 | self.addParameter(name='endTime', value=endTime) |
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320 | 320 | |
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321 | 321 | for key, value in kwargs.items(): |
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322 | 322 | self.addParameter(name=key, value=value) |
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323 | 323 | |
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324 | 324 | |
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325 | 325 | class Project(Process): |
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326 | 326 | """API to create signal chain projects""" |
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327 | 327 | |
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328 | 328 | ELEMENTNAME = 'Project' |
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329 | 329 | |
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330 | 330 | def __init__(self, name=''): |
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331 | 331 | |
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332 | 332 | Process.__init__(self) |
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333 | 333 | self.id = '1' |
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334 | 334 | if name: |
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335 | 335 | self.name = '{} ({})'.format(Process.__name__, name) |
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336 | 336 | self.filename = None |
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337 | 337 | self.description = None |
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338 | 338 | self.email = None |
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339 | 339 | self.alarm = [] |
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340 | 340 | self.configurations = {} |
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341 | 341 | # self.err_queue = Queue() |
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342 | 342 | self.err_queue = None |
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343 | 343 | self.started = False |
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344 | 344 | |
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345 | 345 | def getNewId(self): |
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346 | 346 | |
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347 | 347 | idList = list(self.configurations.keys()) |
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348 | 348 | id = int(self.id) * 10 |
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349 | 349 | |
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350 | 350 | while True: |
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351 | 351 | id += 1 |
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352 | 352 | |
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353 | 353 | if str(id) in idList: |
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354 | 354 | continue |
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355 | 355 | |
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356 | 356 | break |
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357 | 357 | |
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358 | 358 | return str(id) |
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359 | 359 | |
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360 | 360 | def updateId(self, new_id): |
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361 | 361 | |
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362 | 362 | self.id = str(new_id) |
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363 | 363 | |
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364 | 364 | keyList = list(self.configurations.keys()) |
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365 | 365 | keyList.sort() |
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366 | 366 | |
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367 | 367 | n = 1 |
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368 | 368 | new_confs = {} |
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369 | 369 | |
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370 | 370 | for procKey in keyList: |
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371 | 371 | |
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372 | 372 | conf = self.configurations[procKey] |
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373 | 373 | idProcUnit = str(int(self.id) * 10 + n) |
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374 | 374 | conf.updateId(idProcUnit) |
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375 | 375 | new_confs[idProcUnit] = conf |
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376 | 376 | n += 1 |
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377 | 377 | |
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378 | 378 | self.configurations = new_confs |
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379 | 379 | |
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380 | 380 | def setup(self, id=1, name='', description='', email=None, alarm=[]): |
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381 | 381 | |
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382 | 382 | self.id = str(id) |
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383 | 383 | self.description = description |
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384 | 384 | self.email = email |
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385 | 385 | self.alarm = alarm |
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386 | 386 | if name: |
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387 | 387 | self.name = '{} ({})'.format(Process.__name__, name) |
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388 | 388 | |
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389 | 389 | def update(self, **kwargs): |
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390 | 390 | |
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391 | 391 | for key, value in kwargs.items(): |
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392 | 392 | setattr(self, key, value) |
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393 | 393 | |
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394 | 394 | def clone(self): |
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395 | 395 | |
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396 | 396 | p = Project() |
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397 | 397 | p.id = self.id |
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398 | 398 | p.name = self.name |
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399 | 399 | p.description = self.description |
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400 | 400 | p.configurations = self.configurations.copy() |
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401 | 401 | |
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402 | 402 | return p |
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403 | 403 | |
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404 | 404 | def addReadUnit(self, id=None, datatype=None, name=None, **kwargs): |
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405 | 405 | |
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406 | 406 | ''' |
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407 | 407 | ''' |
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408 | 408 | |
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409 | 409 | if id is None: |
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410 | 410 | idReadUnit = self.getNewId() |
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411 | 411 | else: |
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412 | 412 | idReadUnit = str(id) |
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413 | 413 | |
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414 | 414 | conf = ReadUnitConf() |
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415 | 415 | conf.setup(self.id, idReadUnit, name, datatype, self.err_queue, **kwargs) |
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416 | 416 | self.configurations[conf.id] = conf |
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417 | 417 | |
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418 | 418 | return conf |
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419 | 419 | |
|
|
420 | 420 | def addProcUnit(self, id=None, inputId='0', datatype=None, name=None): |
|
|
421 | 421 | |
|
|
422 | 422 | ''' |
|
|
423 | 423 | ''' |
|
|
424 | 424 | |
|
|
425 | 425 | if id is None: |
|
|
426 | 426 | idProcUnit = self.getNewId() |
|
|
427 | 427 | else: |
|
|
428 | 428 | idProcUnit = id |
|
|
429 | 429 | |
|
|
430 | 430 | conf = ProcUnitConf() |
|
|
431 | 431 | conf.setup(self.id, idProcUnit, name, datatype, inputId, self.err_queue) |
|
|
432 | 432 | self.configurations[conf.id] = conf |
|
|
433 | 433 | |
|
|
434 | 434 | return conf |
|
|
435 | 435 | |
|
|
436 | 436 | def removeProcUnit(self, id): |
|
|
437 | 437 | |
|
|
438 | 438 | if id in self.configurations: |
|
|
439 | 439 | self.configurations.pop(id) |
|
|
440 | 440 | |
|
|
441 | 441 | def getReadUnit(self): |
|
|
442 | 442 | |
|
|
443 | 443 | for obj in list(self.configurations.values()): |
|
|
444 | 444 | if obj.ELEMENTNAME == 'ReadUnit': |
|
|
445 | 445 | return obj |
|
|
446 | 446 | |
|
|
447 | 447 | return None |
|
|
448 | 448 | |
|
|
449 | 449 | def getProcUnit(self, id): |
|
|
450 | 450 | |
|
|
451 | 451 | return self.configurations[id] |
|
|
452 | 452 | |
|
|
453 | 453 | def getUnits(self): |
|
|
454 | 454 | |
|
|
455 | 455 | keys = list(self.configurations) |
|
|
456 | 456 | keys.sort() |
|
|
457 | 457 | |
|
|
458 | 458 | for key in keys: |
|
|
459 | 459 | yield self.configurations[key] |
|
|
460 | 460 | |
|
|
461 | 461 | def updateUnit(self, id, **kwargs): |
|
|
462 | 462 | |
|
|
463 | 463 | conf = self.configurations[id].update(**kwargs) |
|
|
464 | 464 | |
|
|
465 | 465 | def makeXml(self): |
|
|
466 | 466 | |
|
|
467 | 467 | xml = Element('Project') |
|
|
468 | 468 | xml.set('id', str(self.id)) |
|
|
469 | 469 | xml.set('name', self.name) |
|
|
470 | 470 | xml.set('description', self.description) |
|
|
471 | 471 | |
|
|
472 | 472 | for conf in self.configurations.values(): |
|
|
473 | 473 | conf.makeXml(xml) |
|
|
474 | 474 | |
|
|
475 | 475 | self.xml = xml |
|
|
476 | 476 | |
|
|
477 | 477 | def writeXml(self, filename=None): |
|
|
478 | 478 | |
|
|
479 | 479 | if filename == None: |
|
|
480 | 480 | if self.filename: |
|
|
481 | 481 | filename = self.filename |
|
|
482 | 482 | else: |
|
|
483 | 483 | filename = 'schain.xml' |
|
|
484 | 484 | |
|
|
485 | 485 | if not filename: |
|
|
486 | 486 | print('filename has not been defined. Use setFilename(filename) for do it.') |
|
|
487 | 487 | return 0 |
|
|
488 | 488 | |
|
|
489 | 489 | abs_file = os.path.abspath(filename) |
|
|
490 | 490 | |
|
|
491 | 491 | if not os.access(os.path.dirname(abs_file), os.W_OK): |
|
|
492 | 492 | print('No write permission on %s' % os.path.dirname(abs_file)) |
|
|
493 | 493 | return 0 |
|
|
494 | 494 | |
|
|
495 | 495 | if os.path.isfile(abs_file) and not(os.access(abs_file, os.W_OK)): |
|
|
496 | 496 | print('File %s already exists and it could not be overwriten' % abs_file) |
|
|
497 | 497 | return 0 |
|
|
498 | 498 | |
|
|
499 | 499 | self.makeXml() |
|
|
500 | 500 | |
|
|
501 | 501 | ElementTree(self.xml).write(abs_file, method='xml') |
|
|
502 | 502 | |
|
|
503 | 503 | self.filename = abs_file |
|
|
504 | 504 | |
|
|
505 | 505 | return 1 |
|
|
506 | 506 | |
|
|
507 | 507 | def readXml(self, filename): |
|
|
508 | 508 | |
|
|
509 | 509 | abs_file = os.path.abspath(filename) |
|
|
510 | 510 | |
|
|
511 | 511 | self.configurations = {} |
|
|
512 | 512 | |
|
|
513 | 513 | try: |
|
|
514 | 514 | self.xml = ElementTree().parse(abs_file) |
|
|
515 | 515 | except: |
|
|
516 | 516 | log.error('Error reading %s, verify file format' % filename) |
|
|
517 | 517 | return 0 |
|
|
518 | 518 | |
|
|
519 | 519 | self.id = self.xml.get('id') |
|
|
520 | 520 | self.name = self.xml.get('name') |
|
|
521 | 521 | self.description = self.xml.get('description') |
|
|
522 | 522 | |
|
|
523 | 523 | for element in self.xml: |
|
|
524 | 524 | if element.tag == 'ReadUnit': |
|
|
525 | 525 | conf = ReadUnitConf() |
|
|
526 | 526 | conf.readXml(element, self.id, self.err_queue) |
|
|
527 | 527 | self.configurations[conf.id] = conf |
|
|
528 | 528 | elif element.tag == 'ProcUnit': |
|
|
529 | 529 | conf = ProcUnitConf() |
|
|
530 | 530 | input_proc = self.configurations[element.get('inputId')] |
|
|
531 | 531 | conf.readXml(element, self.id, self.err_queue) |
|
|
532 | 532 | self.configurations[conf.id] = conf |
|
|
533 | 533 | |
|
|
534 | 534 | self.filename = abs_file |
|
|
535 | 535 | |
|
|
536 | 536 | return 1 |
|
|
537 | 537 | |
|
|
538 | 538 | def __str__(self): |
|
|
539 | 539 | |
|
|
540 | 540 | text = '\nProject[id=%s, name=%s, description=%s]\n\n' % ( |
|
|
541 | 541 | self.id, |
|
|
542 | 542 | self.name, |
|
|
543 | 543 | self.description, |
|
|
544 | 544 | ) |
|
|
545 | 545 | |
|
|
546 | 546 | for conf in self.configurations.values(): |
|
|
547 | 547 | text += '{}'.format(conf) |
|
|
548 | 548 | |
|
|
549 | 549 | return text |
|
|
550 | 550 | |
|
|
551 | 551 | def createObjects(self): |
|
|
552 | 552 | |
|
|
553 | 553 | keys = list(self.configurations.keys()) |
|
|
554 | 554 | keys.sort() |
|
|
555 | 555 | for key in keys: |
|
|
556 | 556 | conf = self.configurations[key] |
|
|
557 | 557 | conf.createObjects() |
|
|
558 | 558 | if conf.inputId is not None: |
|
|
559 | conf.object.setInput(self.configurations[conf.inputId].object) | |
|
|
559 | if isinstance(conf.inputId, list): | |
|
|
560 | conf.object.setInput([self.configurations[x].object for x in conf.inputId]) | |
|
|
561 | else: | |
|
|
562 | conf.object.setInput([self.configurations[conf.inputId].object]) | |
|
|
560 | 563 | |
|
|
561 | 564 | def monitor(self): |
|
|
562 | 565 | |
|
|
563 | 566 | t = Thread(target=self._monitor, args=(self.err_queue, self.ctx)) |
|
|
564 | 567 | t.start() |
|
|
565 | 568 | |
|
|
566 | 569 | def _monitor(self, queue, ctx): |
|
|
567 | 570 | |
|
|
568 | 571 | import socket |
|
|
569 | 572 | |
|
|
570 | 573 | procs = 0 |
|
|
571 | 574 | err_msg = '' |
|
|
572 | 575 | |
|
|
573 | 576 | while True: |
|
|
574 | 577 | msg = queue.get() |
|
|
575 | 578 | if '#_start_#' in msg: |
|
|
576 | 579 | procs += 1 |
|
|
577 | 580 | elif '#_end_#' in msg: |
|
|
578 | 581 | procs -=1 |
|
|
579 | 582 | else: |
|
|
580 | 583 | err_msg = msg |
|
|
581 | 584 | |
|
|
582 | 585 | if procs == 0 or 'Traceback' in err_msg: |
|
|
583 | 586 | break |
|
|
584 | 587 | time.sleep(0.1) |
|
|
585 | 588 | |
|
|
586 | 589 | if '|' in err_msg: |
|
|
587 | 590 | name, err = err_msg.split('|') |
|
|
588 | 591 | if 'SchainWarning' in err: |
|
|
589 | 592 | log.warning(err.split('SchainWarning:')[-1].split('\n')[0].strip(), name) |
|
|
590 | 593 | elif 'SchainError' in err: |
|
|
591 | 594 | log.error(err.split('SchainError:')[-1].split('\n')[0].strip(), name) |
|
|
592 | 595 | else: |
|
|
593 | 596 | log.error(err, name) |
|
|
594 | 597 | else: |
|
|
595 | 598 | name, err = self.name, err_msg |
|
|
596 | 599 | |
|
|
597 | 600 | time.sleep(1) |
|
|
598 | 601 | |
|
|
599 | 602 | ctx.term() |
|
|
600 | 603 | |
|
|
601 | 604 | message = ''.join(err) |
|
|
602 | 605 | |
|
|
603 | 606 | if err_msg: |
|
|
604 | 607 | subject = 'SChain v%s: Error running %s\n' % ( |
|
|
605 | 608 | schainpy.__version__, self.name) |
|
|
606 | 609 | |
|
|
607 | 610 | subtitle = 'Hostname: %s\n' % socket.gethostbyname( |
|
|
608 | 611 | socket.gethostname()) |
|
|
609 | 612 | subtitle += 'Working directory: %s\n' % os.path.abspath('./') |
|
|
610 | 613 | subtitle += 'Configuration file: %s\n' % self.filename |
|
|
611 | 614 | subtitle += 'Time: %s\n' % str(datetime.datetime.now()) |
|
|
612 | 615 | |
|
|
613 | 616 | readUnitConfObj = self.getReadUnit() |
|
|
614 | 617 | if readUnitConfObj: |
|
|
615 | 618 | subtitle += '\nInput parameters:\n' |
|
|
616 | 619 | subtitle += '[Data path = %s]\n' % readUnitConfObj.parameters['path'] |
|
|
617 | 620 | subtitle += '[Start date = %s]\n' % readUnitConfObj.parameters['startDate'] |
|
|
618 | 621 | subtitle += '[End date = %s]\n' % readUnitConfObj.parameters['endDate'] |
|
|
619 | 622 | subtitle += '[Start time = %s]\n' % readUnitConfObj.parameters['startTime'] |
|
|
620 | 623 | subtitle += '[End time = %s]\n' % readUnitConfObj.parameters['endTime'] |
|
|
621 | 624 | |
|
|
622 | 625 | a = Alarm( |
|
|
623 | 626 | modes=self.alarm, |
|
|
624 | 627 | email=self.email, |
|
|
625 | 628 | message=message, |
|
|
626 | 629 | subject=subject, |
|
|
627 | 630 | subtitle=subtitle, |
|
|
628 | 631 | filename=self.filename |
|
|
629 | 632 | ) |
|
|
630 | 633 | |
|
|
631 | 634 | a.start() |
|
|
632 | 635 | |
|
|
633 | 636 | def setFilename(self, filename): |
|
|
634 | 637 | |
|
|
635 | 638 | self.filename = filename |
|
|
636 | 639 | |
|
|
637 | 640 | def runProcs(self): |
|
|
638 | 641 | |
|
|
639 | 642 | err = False |
|
|
640 | 643 | n = len(self.configurations) |
|
|
641 | 644 | |
|
|
642 | 645 | while not err: |
|
|
643 | 646 | for conf in self.getUnits(): |
|
|
644 | 647 | ok = conf.run() |
|
|
645 | 648 | if ok == 'Error': |
|
|
646 | 649 | n -= 1 |
|
|
647 | 650 | continue |
|
|
648 | 651 | elif not ok: |
|
|
649 | 652 | break |
|
|
650 | 653 | if n == 0: |
|
|
651 | 654 | err = True |
|
|
652 | 655 | |
|
|
653 | 656 | def run(self): |
|
|
654 | 657 | |
|
|
655 | 658 | log.success('\nStarting Project {} [id={}]'.format(self.name, self.id), tag='') |
|
|
656 | 659 | self.started = True |
|
|
657 | 660 | self.start_time = time.time() |
|
|
658 | 661 | self.createObjects() |
|
|
659 | 662 | self.runProcs() |
|
|
660 | 663 | log.success('{} Done (Time: {:4.2f}s)'.format( |
|
|
661 | 664 | self.name, |
|
|
662 | 665 | time.time()-self.start_time), '') |
| @@ -1,1788 +1,1788 | |||
|
|
1 | 1 | import os |
|
|
2 | 2 | import datetime |
|
|
3 | 3 | import numpy |
|
|
4 | 4 | from mpl_toolkits.axisartist.grid_finder import FixedLocator, DictFormatter |
|
|
5 | 5 | |
|
|
6 | 6 | from schainpy.model.graphics.jroplot_base import Plot, plt |
|
|
7 | 7 | from schainpy.model.graphics.jroplot_spectra import SpectraPlot, RTIPlot, CoherencePlot, SpectraCutPlot |
|
|
8 | 8 | from schainpy.utils import log |
|
|
9 | 9 | # libreria wradlib |
|
|
10 | 10 | import wradlib as wrl |
|
|
11 | 11 | |
|
|
12 | 12 | EARTH_RADIUS = 6.3710e3 |
|
|
13 | 13 | |
|
|
14 | 14 | |
|
|
15 | 15 | def ll2xy(lat1, lon1, lat2, lon2): |
|
|
16 | 16 | |
|
|
17 | 17 | p = 0.017453292519943295 |
|
|
18 | 18 | a = 0.5 - numpy.cos((lat2 - lat1) * p)/2 + numpy.cos(lat1 * p) * \ |
|
|
19 | 19 | numpy.cos(lat2 * p) * (1 - numpy.cos((lon2 - lon1) * p)) / 2 |
|
|
20 | 20 | r = 12742 * numpy.arcsin(numpy.sqrt(a)) |
|
|
21 | 21 | theta = numpy.arctan2(numpy.sin((lon2-lon1)*p)*numpy.cos(lat2*p), numpy.cos(lat1*p) |
|
|
22 | 22 | * numpy.sin(lat2*p)-numpy.sin(lat1*p)*numpy.cos(lat2*p)*numpy.cos((lon2-lon1)*p)) |
|
|
23 | 23 | theta = -theta + numpy.pi/2 |
|
|
24 | 24 | return r*numpy.cos(theta), r*numpy.sin(theta) |
|
|
25 | 25 | |
|
|
26 | 26 | |
|
|
27 | 27 | def km2deg(km): |
|
|
28 | 28 | ''' |
|
|
29 | 29 | Convert distance in km to degrees |
|
|
30 | 30 | ''' |
|
|
31 | 31 | |
|
|
32 | 32 | return numpy.rad2deg(km/EARTH_RADIUS) |
|
|
33 | 33 | |
|
|
34 | 34 | |
|
|
35 | 35 | |
|
|
36 | 36 | class SpectralMomentsPlot(SpectraPlot): |
|
|
37 | 37 | ''' |
|
|
38 | 38 | Plot for Spectral Moments |
|
|
39 | 39 | ''' |
|
|
40 | 40 | CODE = 'spc_moments' |
|
|
41 | 41 | # colormap = 'jet' |
|
|
42 | 42 | # plot_type = 'pcolor' |
|
|
43 | 43 | |
|
|
44 | 44 | class DobleGaussianPlot(SpectraPlot): |
|
|
45 | 45 | ''' |
|
|
46 | 46 | Plot for Double Gaussian Plot |
|
|
47 | 47 | ''' |
|
|
48 | 48 | CODE = 'gaussian_fit' |
|
|
49 | 49 | # colormap = 'jet' |
|
|
50 | 50 | # plot_type = 'pcolor' |
|
|
51 | 51 | |
|
|
52 | 52 | class DoubleGaussianSpectraCutPlot(SpectraCutPlot): |
|
|
53 | 53 | ''' |
|
|
54 | 54 | Plot SpectraCut with Double Gaussian Fit |
|
|
55 | 55 | ''' |
|
|
56 | 56 | CODE = 'cut_gaussian_fit' |
|
|
57 | 57 | |
|
|
58 | 58 | class SnrPlot(RTIPlot): |
|
|
59 | 59 | ''' |
|
|
60 | 60 | Plot for SNR Data |
|
|
61 | 61 | ''' |
|
|
62 | 62 | |
|
|
63 | 63 | CODE = 'snr' |
|
|
64 | 64 | colormap = 'jet' |
|
|
65 | 65 | |
|
|
66 | 66 | def update(self, dataOut): |
|
|
67 | 67 | |
|
|
68 | 68 | data = { |
|
|
69 | 69 | 'snr': 10*numpy.log10(dataOut.data_snr) |
|
|
70 | 70 | } |
|
|
71 | 71 | |
|
|
72 | 72 | return data, {} |
|
|
73 | 73 | |
|
|
74 | 74 | class DopplerPlot(RTIPlot): |
|
|
75 | 75 | ''' |
|
|
76 | 76 | Plot for DOPPLER Data (1st moment) |
|
|
77 | 77 | ''' |
|
|
78 | 78 | |
|
|
79 | 79 | CODE = 'dop' |
|
|
80 | 80 | colormap = 'jet' |
|
|
81 | 81 | |
|
|
82 | 82 | def update(self, dataOut): |
|
|
83 | 83 | |
|
|
84 | 84 | data = { |
|
|
85 | 85 | 'dop': 10*numpy.log10(dataOut.data_dop) |
|
|
86 | 86 | } |
|
|
87 | 87 | |
|
|
88 | 88 | return data, {} |
|
|
89 | 89 | |
|
|
90 | 90 | class PowerPlot(RTIPlot): |
|
|
91 | 91 | ''' |
|
|
92 | 92 | Plot for Power Data (0 moment) |
|
|
93 | 93 | ''' |
|
|
94 | 94 | |
|
|
95 | 95 | CODE = 'pow' |
|
|
96 | 96 | colormap = 'jet' |
|
|
97 | 97 | |
|
|
98 | 98 | def update(self, dataOut): |
|
|
99 | 99 | data = { |
|
|
100 | 100 | 'pow': 10*numpy.log10(dataOut.data_pow/dataOut.normFactor) |
|
|
101 | 101 | } |
|
|
102 | 102 | return data, {} |
|
|
103 | 103 | |
|
|
104 | 104 | class SpectralWidthPlot(RTIPlot): |
|
|
105 | 105 | ''' |
|
|
106 | 106 | Plot for Spectral Width Data (2nd moment) |
|
|
107 | 107 | ''' |
|
|
108 | 108 | |
|
|
109 | 109 | CODE = 'width' |
|
|
110 | 110 | colormap = 'jet' |
|
|
111 | 111 | |
|
|
112 | 112 | def update(self, dataOut): |
|
|
113 | 113 | |
|
|
114 | 114 | data = { |
|
|
115 | 115 | 'width': dataOut.data_width |
|
|
116 | 116 | } |
|
|
117 | 117 | |
|
|
118 | 118 | return data, {} |
|
|
119 | 119 | |
|
|
120 | 120 | class SkyMapPlot(Plot): |
|
|
121 | 121 | ''' |
|
|
122 | 122 | Plot for meteors detection data |
|
|
123 | 123 | ''' |
|
|
124 | 124 | |
|
|
125 | 125 | CODE = 'param' |
|
|
126 | 126 | |
|
|
127 | 127 | def setup(self): |
|
|
128 | 128 | |
|
|
129 | 129 | self.ncols = 1 |
|
|
130 | 130 | self.nrows = 1 |
|
|
131 | 131 | self.width = 7.2 |
|
|
132 | 132 | self.height = 7.2 |
|
|
133 | 133 | self.nplots = 1 |
|
|
134 | 134 | self.xlabel = 'Zonal Zenith Angle (deg)' |
|
|
135 | 135 | self.ylabel = 'Meridional Zenith Angle (deg)' |
|
|
136 | 136 | self.polar = True |
|
|
137 | 137 | self.ymin = -180 |
|
|
138 | 138 | self.ymax = 180 |
|
|
139 | 139 | self.colorbar = False |
|
|
140 | 140 | |
|
|
141 | 141 | def plot(self): |
|
|
142 | 142 | |
|
|
143 | 143 | arrayParameters = numpy.concatenate(self.data['param']) |
|
|
144 | 144 | error = arrayParameters[:, -1] |
|
|
145 | 145 | indValid = numpy.where(error == 0)[0] |
|
|
146 | 146 | finalMeteor = arrayParameters[indValid, :] |
|
|
147 | 147 | finalAzimuth = finalMeteor[:, 3] |
|
|
148 | 148 | finalZenith = finalMeteor[:, 4] |
|
|
149 | 149 | |
|
|
150 | 150 | x = finalAzimuth * numpy.pi / 180 |
|
|
151 | 151 | y = finalZenith |
|
|
152 | 152 | |
|
|
153 | 153 | ax = self.axes[0] |
|
|
154 | 154 | |
|
|
155 | 155 | if ax.firsttime: |
|
|
156 | 156 | ax.plot = ax.plot(x, y, 'bo', markersize=5)[0] |
|
|
157 | 157 | else: |
|
|
158 | 158 | ax.plot.set_data(x, y) |
|
|
159 | 159 | |
|
|
160 | 160 | dt1 = self.getDateTime(self.data.min_time).strftime('%y/%m/%d %H:%M:%S') |
|
|
161 | 161 | dt2 = self.getDateTime(self.data.max_time).strftime('%y/%m/%d %H:%M:%S') |
|
|
162 | 162 | title = 'Meteor Detection Sky Map\n %s - %s \n Number of events: %5.0f\n' % (dt1, |
|
|
163 | 163 | dt2, |
|
|
164 | 164 | len(x)) |
|
|
165 | 165 | self.titles[0] = title |
|
|
166 | 166 | |
|
|
167 | 167 | |
|
|
168 | 168 | class GenericRTIPlot(Plot): |
|
|
169 | 169 | ''' |
|
|
170 | 170 | Plot for data_xxxx object |
|
|
171 | 171 | ''' |
|
|
172 | 172 | |
|
|
173 | 173 | CODE = 'param' |
|
|
174 | 174 | colormap = 'viridis' |
|
|
175 | 175 | plot_type = 'pcolorbuffer' |
|
|
176 | 176 | |
|
|
177 | 177 | def setup(self): |
|
|
178 | 178 | self.xaxis = 'time' |
|
|
179 | 179 | self.ncols = 1 |
|
|
180 | 180 | self.nrows = self.data.shape('param')[0] |
|
|
181 | 181 | self.nplots = self.nrows |
|
|
182 | 182 | self.plots_adjust.update({'hspace':0.8, 'left': 0.1, 'bottom': 0.08, 'right':0.95, 'top': 0.95}) |
|
|
183 | 183 | |
|
|
184 | 184 | if not self.xlabel: |
|
|
185 | 185 | self.xlabel = 'Time' |
|
|
186 | 186 | |
|
|
187 | 187 | self.ylabel = 'Range [km]' |
|
|
188 | 188 | if not self.titles: |
|
|
189 | 189 | self.titles = ['Param {}'.format(x) for x in range(self.nrows)] |
|
|
190 | 190 | |
|
|
191 | 191 | def update(self, dataOut): |
|
|
192 | 192 | |
|
|
193 | 193 | data = { |
|
|
194 | 194 | 'param' : numpy.concatenate([getattr(dataOut, attr) for attr in self.attr_data], axis=0) |
|
|
195 | 195 | } |
|
|
196 | 196 | |
|
|
197 | 197 | meta = {} |
|
|
198 | 198 | |
|
|
199 | 199 | return data, meta |
|
|
200 | 200 | |
|
|
201 | 201 | def plot(self): |
|
|
202 | 202 | # self.data.normalize_heights() |
|
|
203 | 203 | self.x = self.data.times |
|
|
204 | 204 | self.y = self.data.yrange |
|
|
205 | 205 | self.z = self.data['param'] |
|
|
206 | 206 | self.z = 10*numpy.log10(self.z) |
|
|
207 | 207 | self.z = numpy.ma.masked_invalid(self.z) |
|
|
208 | 208 | |
|
|
209 | 209 | if self.decimation is None: |
|
|
210 | 210 | x, y, z = self.fill_gaps(self.x, self.y, self.z) |
|
|
211 | 211 | else: |
|
|
212 | 212 | x, y, z = self.fill_gaps(*self.decimate()) |
|
|
213 | 213 | |
|
|
214 | 214 | for n, ax in enumerate(self.axes): |
|
|
215 | 215 | |
|
|
216 | 216 | self.zmax = self.zmax if self.zmax is not None else numpy.max( |
|
|
217 | 217 | self.z[n]) |
|
|
218 | 218 | self.zmin = self.zmin if self.zmin is not None else numpy.min( |
|
|
219 | 219 | self.z[n]) |
|
|
220 | 220 | |
|
|
221 | 221 | if ax.firsttime: |
|
|
222 | 222 | if self.zlimits is not None: |
|
|
223 | 223 | self.zmin, self.zmax = self.zlimits[n] |
|
|
224 | 224 | |
|
|
225 | 225 | ax.plt = ax.pcolormesh(x, y, z[n].T * self.factors[n], |
|
|
226 | 226 | vmin=self.zmin, |
|
|
227 | 227 | vmax=self.zmax, |
|
|
228 | 228 | cmap=self.cmaps[n] |
|
|
229 | 229 | ) |
|
|
230 | 230 | else: |
|
|
231 | 231 | if self.zlimits is not None: |
|
|
232 | 232 | self.zmin, self.zmax = self.zlimits[n] |
|
|
233 | 233 | ax.collections.remove(ax.collections[0]) |
|
|
234 | 234 | ax.plt = ax.pcolormesh(x, y, z[n].T * self.factors[n], |
|
|
235 | 235 | vmin=self.zmin, |
|
|
236 | 236 | vmax=self.zmax, |
|
|
237 | 237 | cmap=self.cmaps[n] |
|
|
238 | 238 | ) |
|
|
239 | 239 | |
|
|
240 | 240 | |
|
|
241 | 241 | class PolarMapPlot(Plot): |
|
|
242 | 242 | ''' |
|
|
243 | 243 | Plot for weather radar |
|
|
244 | 244 | ''' |
|
|
245 | 245 | |
|
|
246 | 246 | CODE = 'param' |
|
|
247 | 247 | colormap = 'seismic' |
|
|
248 | 248 | |
|
|
249 | 249 | def setup(self): |
|
|
250 | 250 | self.ncols = 1 |
|
|
251 | 251 | self.nrows = 1 |
|
|
252 | 252 | self.width = 9 |
|
|
253 | 253 | self.height = 8 |
|
|
254 | 254 | self.mode = self.data.meta['mode'] |
|
|
255 | 255 | if self.channels is not None: |
|
|
256 | 256 | self.nplots = len(self.channels) |
|
|
257 | 257 | self.nrows = len(self.channels) |
|
|
258 | 258 | else: |
|
|
259 | 259 | self.nplots = self.data.shape(self.CODE)[0] |
|
|
260 | 260 | self.nrows = self.nplots |
|
|
261 | 261 | self.channels = list(range(self.nplots)) |
|
|
262 | 262 | if self.mode == 'E': |
|
|
263 | 263 | self.xlabel = 'Longitude' |
|
|
264 | 264 | self.ylabel = 'Latitude' |
|
|
265 | 265 | else: |
|
|
266 | 266 | self.xlabel = 'Range (km)' |
|
|
267 | 267 | self.ylabel = 'Height (km)' |
|
|
268 | 268 | self.bgcolor = 'white' |
|
|
269 | 269 | self.cb_labels = self.data.meta['units'] |
|
|
270 | 270 | self.lat = self.data.meta['latitude'] |
|
|
271 | 271 | self.lon = self.data.meta['longitude'] |
|
|
272 | 272 | self.xmin, self.xmax = float( |
|
|
273 | 273 | km2deg(self.xmin) + self.lon), float(km2deg(self.xmax) + self.lon) |
|
|
274 | 274 | self.ymin, self.ymax = float( |
|
|
275 | 275 | km2deg(self.ymin) + self.lat), float(km2deg(self.ymax) + self.lat) |
|
|
276 | 276 | # self.polar = True |
|
|
277 | 277 | |
|
|
278 | 278 | def plot(self): |
|
|
279 | 279 | |
|
|
280 | 280 | for n, ax in enumerate(self.axes): |
|
|
281 | 281 | data = self.data['param'][self.channels[n]] |
|
|
282 | 282 | |
|
|
283 | 283 | zeniths = numpy.linspace( |
|
|
284 | 284 | 0, self.data.meta['max_range'], data.shape[1]) |
|
|
285 | 285 | if self.mode == 'E': |
|
|
286 | 286 | azimuths = -numpy.radians(self.data.yrange)+numpy.pi/2 |
|
|
287 | 287 | r, theta = numpy.meshgrid(zeniths, azimuths) |
|
|
288 | 288 | x, y = r*numpy.cos(theta)*numpy.cos(numpy.radians(self.data.meta['elevation'])), r*numpy.sin( |
|
|
289 | 289 | theta)*numpy.cos(numpy.radians(self.data.meta['elevation'])) |
|
|
290 | 290 | x = km2deg(x) + self.lon |
|
|
291 | 291 | y = km2deg(y) + self.lat |
|
|
292 | 292 | else: |
|
|
293 | 293 | azimuths = numpy.radians(self.data.yrange) |
|
|
294 | 294 | r, theta = numpy.meshgrid(zeniths, azimuths) |
|
|
295 | 295 | x, y = r*numpy.cos(theta), r*numpy.sin(theta) |
|
|
296 | 296 | self.y = zeniths |
|
|
297 | 297 | |
|
|
298 | 298 | if ax.firsttime: |
|
|
299 | 299 | if self.zlimits is not None: |
|
|
300 | 300 | self.zmin, self.zmax = self.zlimits[n] |
|
|
301 | 301 | ax.plt = ax.pcolormesh( # r, theta, numpy.ma.array(data, mask=numpy.isnan(data)), |
|
|
302 | 302 | x, y, numpy.ma.array(data, mask=numpy.isnan(data)), |
|
|
303 | 303 | vmin=self.zmin, |
|
|
304 | 304 | vmax=self.zmax, |
|
|
305 | 305 | cmap=self.cmaps[n]) |
|
|
306 | 306 | else: |
|
|
307 | 307 | if self.zlimits is not None: |
|
|
308 | 308 | self.zmin, self.zmax = self.zlimits[n] |
|
|
309 | 309 | ax.collections.remove(ax.collections[0]) |
|
|
310 | 310 | ax.plt = ax.pcolormesh( # r, theta, numpy.ma.array(data, mask=numpy.isnan(data)), |
|
|
311 | 311 | x, y, numpy.ma.array(data, mask=numpy.isnan(data)), |
|
|
312 | 312 | vmin=self.zmin, |
|
|
313 | 313 | vmax=self.zmax, |
|
|
314 | 314 | cmap=self.cmaps[n]) |
|
|
315 | 315 | |
|
|
316 | 316 | if self.mode == 'A': |
|
|
317 | 317 | continue |
|
|
318 | 318 | |
|
|
319 | 319 | # plot district names |
|
|
320 | 320 | f = open('/data/workspace/schain_scripts/distrito.csv') |
|
|
321 | 321 | for line in f: |
|
|
322 | 322 | label, lon, lat = [s.strip() for s in line.split(',') if s] |
|
|
323 | 323 | lat = float(lat) |
|
|
324 | 324 | lon = float(lon) |
|
|
325 | 325 | # ax.plot(lon, lat, '.b', ms=2) |
|
|
326 | 326 | ax.text(lon, lat, label.decode('utf8'), ha='center', |
|
|
327 | 327 | va='bottom', size='8', color='black') |
|
|
328 | 328 | |
|
|
329 | 329 | # plot limites |
|
|
330 | 330 | limites = [] |
|
|
331 | 331 | tmp = [] |
|
|
332 | 332 | for line in open('/data/workspace/schain_scripts/lima.csv'): |
|
|
333 | 333 | if '#' in line: |
|
|
334 | 334 | if tmp: |
|
|
335 | 335 | limites.append(tmp) |
|
|
336 | 336 | tmp = [] |
|
|
337 | 337 | continue |
|
|
338 | 338 | values = line.strip().split(',') |
|
|
339 | 339 | tmp.append((float(values[0]), float(values[1]))) |
|
|
340 | 340 | for points in limites: |
|
|
341 | 341 | ax.add_patch( |
|
|
342 | 342 | Polygon(points, ec='k', fc='none', ls='--', lw=0.5)) |
|
|
343 | 343 | |
|
|
344 | 344 | # plot Cuencas |
|
|
345 | 345 | for cuenca in ('rimac', 'lurin', 'mala', 'chillon', 'chilca', 'chancay-huaral'): |
|
|
346 | 346 | f = open('/data/workspace/schain_scripts/{}.csv'.format(cuenca)) |
|
|
347 | 347 | values = [line.strip().split(',') for line in f] |
|
|
348 | 348 | points = [(float(s[0]), float(s[1])) for s in values] |
|
|
349 | 349 | ax.add_patch(Polygon(points, ec='b', fc='none')) |
|
|
350 | 350 | |
|
|
351 | 351 | # plot grid |
|
|
352 | 352 | for r in (15, 30, 45, 60): |
|
|
353 | 353 | ax.add_artist(plt.Circle((self.lon, self.lat), |
|
|
354 | 354 | km2deg(r), color='0.6', fill=False, lw=0.2)) |
|
|
355 | 355 | ax.text( |
|
|
356 | 356 | self.lon + (km2deg(r))*numpy.cos(60*numpy.pi/180), |
|
|
357 | 357 | self.lat + (km2deg(r))*numpy.sin(60*numpy.pi/180), |
|
|
358 | 358 | '{}km'.format(r), |
|
|
359 | 359 | ha='center', va='bottom', size='8', color='0.6', weight='heavy') |
|
|
360 | 360 | |
|
|
361 | 361 | if self.mode == 'E': |
|
|
362 | 362 | title = 'El={}$^\circ$'.format(self.data.meta['elevation']) |
|
|
363 | 363 | label = 'E{:02d}'.format(int(self.data.meta['elevation'])) |
|
|
364 | 364 | else: |
|
|
365 | 365 | title = 'Az={}$^\circ$'.format(self.data.meta['azimuth']) |
|
|
366 | 366 | label = 'A{:02d}'.format(int(self.data.meta['azimuth'])) |
|
|
367 | 367 | |
|
|
368 | 368 | self.save_labels = ['{}-{}'.format(lbl, label) for lbl in self.labels] |
|
|
369 | 369 | self.titles = ['{} {}'.format( |
|
|
370 | 370 | self.data.parameters[x], title) for x in self.channels] |
|
|
371 | 371 | |
|
|
372 | 372 | class WeatherPlot(Plot): |
|
|
373 | 373 | CODE = 'weather' |
|
|
374 | 374 | plot_name = 'weather' |
|
|
375 | 375 | plot_type = 'ppistyle' |
|
|
376 | 376 | buffering = False |
|
|
377 | 377 | |
|
|
378 | 378 | def setup(self): |
|
|
379 | 379 | self.ncols = 1 |
|
|
380 | 380 | self.nrows = 1 |
|
|
381 | 381 | self.width =8 |
|
|
382 | 382 | self.height =8 |
|
|
383 | 383 | self.nplots= 1 |
|
|
384 | 384 | self.ylabel= 'Range [Km]' |
|
|
385 | 385 | self.titles= ['Weather'] |
|
|
386 | 386 | self.colorbar=False |
|
|
387 | 387 | self.ini =0 |
|
|
388 | 388 | self.len_azi =0 |
|
|
389 | 389 | self.buffer_ini = None |
|
|
390 | 390 | self.buffer_azi = None |
|
|
391 | 391 | self.plots_adjust.update({'wspace': 0.4, 'hspace':0.4, 'left': 0.1, 'right': 0.9, 'bottom': 0.08}) |
|
|
392 | 392 | self.flag =0 |
|
|
393 | 393 | self.indicador= 0 |
|
|
394 | 394 | self.last_data_azi = None |
|
|
395 | 395 | self.val_mean = None |
|
|
396 | 396 | |
|
|
397 | 397 | def update(self, dataOut): |
|
|
398 | 398 | |
|
|
399 | 399 | data = {} |
|
|
400 | 400 | meta = {} |
|
|
401 | 401 | if hasattr(dataOut, 'dataPP_POWER'): |
|
|
402 | 402 | factor = 1 |
|
|
403 | 403 | if hasattr(dataOut, 'nFFTPoints'): |
|
|
404 | 404 | factor = dataOut.normFactor |
|
|
405 | 405 | #print("DIME EL SHAPE PORFAVOR",dataOut.data_360.shape) |
|
|
406 | 406 | data['weather'] = 10*numpy.log10(dataOut.data_360[1]/(factor)) |
|
|
407 | 407 | data['azi'] = dataOut.data_azi |
|
|
408 | 408 | data['ele'] = dataOut.data_ele |
|
|
409 | 409 | return data, meta |
|
|
410 | 410 | |
|
|
411 | 411 | def get2List(self,angulos): |
|
|
412 | 412 | list1=[] |
|
|
413 | 413 | list2=[] |
|
|
414 | 414 | for i in reversed(range(len(angulos))): |
|
|
415 | 415 | diff_ = angulos[i]-angulos[i-1] |
|
|
416 | 416 | if diff_ >1.5: |
|
|
417 | 417 | list1.append(i-1) |
|
|
418 | 418 | list2.append(diff_) |
|
|
419 | 419 | return list(reversed(list1)),list(reversed(list2)) |
|
|
420 | 420 | |
|
|
421 | 421 | def fixData360(self,list_,ang_): |
|
|
422 | 422 | if list_[0]==-1: |
|
|
423 | 423 | vec = numpy.where(ang_<ang_[0]) |
|
|
424 | 424 | ang_[vec] = ang_[vec]+360 |
|
|
425 | 425 | return ang_ |
|
|
426 | 426 | return ang_ |
|
|
427 | 427 | |
|
|
428 | 428 | def fixData360HL(self,angulos): |
|
|
429 | 429 | vec = numpy.where(angulos>=360) |
|
|
430 | 430 | angulos[vec]=angulos[vec]-360 |
|
|
431 | 431 | return angulos |
|
|
432 | 432 | |
|
|
433 | 433 | def search_pos(self,pos,list_): |
|
|
434 | 434 | for i in range(len(list_)): |
|
|
435 | 435 | if pos == list_[i]: |
|
|
436 | 436 | return True,i |
|
|
437 | 437 | i=None |
|
|
438 | 438 | return False,i |
|
|
439 | 439 | |
|
|
440 | 440 | def fixDataComp(self,ang_,list1_,list2_): |
|
|
441 | 441 | size = len(ang_) |
|
|
442 | 442 | size2 = 0 |
|
|
443 | 443 | for i in range(len(list2_)): |
|
|
444 | 444 | size2=size2+round(list2_[i])-1 |
|
|
445 | 445 | new_size= size+size2 |
|
|
446 | 446 | ang_new = numpy.zeros(new_size) |
|
|
447 | 447 | ang_new2 = numpy.zeros(new_size) |
|
|
448 | 448 | |
|
|
449 | 449 | tmp = 0 |
|
|
450 | 450 | c = 0 |
|
|
451 | 451 | for i in range(len(ang_)): |
|
|
452 | 452 | ang_new[tmp +c] = ang_[i] |
|
|
453 | 453 | ang_new2[tmp+c] = ang_[i] |
|
|
454 | 454 | condition , value = self.search_pos(i,list1_) |
|
|
455 | 455 | if condition: |
|
|
456 | 456 | pos = tmp + c + 1 |
|
|
457 | 457 | for k in range(round(list2_[value])-1): |
|
|
458 | 458 | ang_new[pos+k] = ang_new[pos+k-1]+1 |
|
|
459 | 459 | ang_new2[pos+k] = numpy.nan |
|
|
460 | 460 | tmp = pos +k |
|
|
461 | 461 | c = 0 |
|
|
462 | 462 | c=c+1 |
|
|
463 | 463 | return ang_new,ang_new2 |
|
|
464 | 464 | |
|
|
465 | 465 | def globalCheckPED(self,angulos): |
|
|
466 | 466 | l1,l2 = self.get2List(angulos) |
|
|
467 | 467 | if len(l1)>0: |
|
|
468 | 468 | angulos2 = self.fixData360(list_=l1,ang_=angulos) |
|
|
469 | 469 | l1,l2 = self.get2List(angulos2) |
|
|
470 | 470 | |
|
|
471 | 471 | ang1_,ang2_ = self.fixDataComp(ang_=angulos2,list1_=l1,list2_=l2) |
|
|
472 | 472 | ang1_ = self.fixData360HL(ang1_) |
|
|
473 | 473 | ang2_ = self.fixData360HL(ang2_) |
|
|
474 | 474 | else: |
|
|
475 | 475 | ang1_= angulos |
|
|
476 | 476 | ang2_= angulos |
|
|
477 | 477 | return ang1_,ang2_ |
|
|
478 | 478 | |
|
|
479 | 479 | def analizeDATA(self,data_azi): |
|
|
480 | 480 | list1 = [] |
|
|
481 | 481 | list2 = [] |
|
|
482 | 482 | dat = data_azi |
|
|
483 | 483 | for i in reversed(range(1,len(dat))): |
|
|
484 | 484 | if dat[i]>dat[i-1]: |
|
|
485 | 485 | diff = int(dat[i])-int(dat[i-1]) |
|
|
486 | 486 | else: |
|
|
487 | 487 | diff = 360+int(dat[i])-int(dat[i-1]) |
|
|
488 | 488 | if diff > 1: |
|
|
489 | 489 | list1.append(i-1) |
|
|
490 | 490 | list2.append(diff-1) |
|
|
491 | 491 | return list1,list2 |
|
|
492 | 492 | |
|
|
493 | 493 | def fixDATANEW(self,data_azi,data_weather): |
|
|
494 | 494 | list1,list2 = self.analizeDATA(data_azi) |
|
|
495 | 495 | if len(list1)== 0: |
|
|
496 | 496 | return data_azi,data_weather |
|
|
497 | 497 | else: |
|
|
498 | 498 | resize = 0 |
|
|
499 | 499 | for i in range(len(list2)): |
|
|
500 | 500 | resize= resize + list2[i] |
|
|
501 | 501 | new_data_azi = numpy.resize(data_azi,resize) |
|
|
502 | 502 | new_data_weather= numpy.resize(date_weather,resize) |
|
|
503 | 503 | |
|
|
504 | 504 | for i in range(len(list2)): |
|
|
505 | 505 | j=0 |
|
|
506 | 506 | position=list1[i]+1 |
|
|
507 | 507 | for j in range(list2[i]): |
|
|
508 | 508 | new_data_azi[position+j]=new_data_azi[position+j-1]+1 |
|
|
509 | 509 | return new_data_azi |
|
|
510 | 510 | |
|
|
511 | 511 | def fixDATA(self,data_azi): |
|
|
512 | 512 | data=data_azi |
|
|
513 | 513 | for i in range(len(data)): |
|
|
514 | 514 | if numpy.isnan(data[i]): |
|
|
515 | 515 | data[i]=data[i-1]+1 |
|
|
516 | 516 | return data |
|
|
517 | 517 | |
|
|
518 | 518 | def replaceNAN(self,data_weather,data_azi,val): |
|
|
519 | 519 | data= data_azi |
|
|
520 | 520 | data_T= data_weather |
|
|
521 | 521 | if data.shape[0]> data_T.shape[0]: |
|
|
522 | 522 | data_N = numpy.ones( [data.shape[0],data_T.shape[1]]) |
|
|
523 | 523 | c = 0 |
|
|
524 | 524 | for i in range(len(data)): |
|
|
525 | 525 | if numpy.isnan(data[i]): |
|
|
526 | 526 | data_N[i,:]=numpy.ones(data_T.shape[1])*numpy.nan |
|
|
527 | 527 | else: |
|
|
528 | 528 | data_N[i,:]=data_T[c,:] |
|
|
529 | 529 | c=c+1 |
|
|
530 | 530 | return data_N |
|
|
531 | 531 | else: |
|
|
532 | 532 | for i in range(len(data)): |
|
|
533 | 533 | if numpy.isnan(data[i]): |
|
|
534 | 534 | data_T[i,:]=numpy.ones(data_T.shape[1])*numpy.nan |
|
|
535 | 535 | return data_T |
|
|
536 | 536 | |
|
|
537 | 537 | def const_ploteo(self,data_weather,data_azi,step,res): |
|
|
538 | 538 | if self.ini==0: |
|
|
539 | 539 | #------- |
|
|
540 | 540 | n = (360/res)-len(data_azi) |
|
|
541 | 541 | #--------------------- new ------------------------- |
|
|
542 | 542 | data_azi_new ,data_azi_old= self.globalCheckPED(data_azi) |
|
|
543 | 543 | #------------------------ |
|
|
544 | 544 | start = data_azi_new[-1] + res |
|
|
545 | 545 | end = data_azi_new[0] - res |
|
|
546 | 546 | #------ new |
|
|
547 | 547 | self.last_data_azi = end |
|
|
548 | 548 | if start>end: |
|
|
549 | 549 | end = end + 360 |
|
|
550 | 550 | azi_vacia = numpy.linspace(start,end,int(n)) |
|
|
551 | 551 | azi_vacia = numpy.where(azi_vacia>360,azi_vacia-360,azi_vacia) |
|
|
552 | 552 | data_azi = numpy.hstack((data_azi_new,azi_vacia)) |
|
|
553 | 553 | # RADAR |
|
|
554 | 554 | val_mean = numpy.mean(data_weather[:,-1]) |
|
|
555 | 555 | self.val_mean = val_mean |
|
|
556 | 556 | data_weather_cmp = numpy.ones([(360-data_weather.shape[0]),data_weather.shape[1]])*val_mean |
|
|
557 | 557 | data_weather = self.replaceNAN(data_weather=data_weather,data_azi=data_azi_old,val=self.val_mean) |
|
|
558 | 558 | data_weather = numpy.vstack((data_weather,data_weather_cmp)) |
|
|
559 | 559 | else: |
|
|
560 | 560 | # azimuth |
|
|
561 | 561 | flag=0 |
|
|
562 | 562 | start_azi = self.res_azi[0] |
|
|
563 | 563 | #-----------new------------ |
|
|
564 | 564 | data_azi ,data_azi_old= self.globalCheckPED(data_azi) |
|
|
565 | 565 | data_weather = self.replaceNAN(data_weather=data_weather,data_azi=data_azi_old,val=self.val_mean) |
|
|
566 | 566 | #-------------------------- |
|
|
567 | 567 | start = data_azi[0] |
|
|
568 | 568 | end = data_azi[-1] |
|
|
569 | 569 | self.last_data_azi= end |
|
|
570 | 570 | if start< start_azi: |
|
|
571 | 571 | start = start +360 |
|
|
572 | 572 | if end <start_azi: |
|
|
573 | 573 | end = end +360 |
|
|
574 | 574 | |
|
|
575 | 575 | pos_ini = int((start-start_azi)/res) |
|
|
576 | 576 | len_azi = len(data_azi) |
|
|
577 | 577 | if (360-pos_ini)<len_azi: |
|
|
578 | 578 | if pos_ini+1==360: |
|
|
579 | 579 | pos_ini=0 |
|
|
580 | 580 | else: |
|
|
581 | 581 | flag=1 |
|
|
582 | 582 | dif= 360-pos_ini |
|
|
583 | 583 | comp= len_azi-dif |
|
|
584 | 584 | #----------------- |
|
|
585 | 585 | if flag==0: |
|
|
586 | 586 | # AZIMUTH |
|
|
587 | 587 | self.res_azi[pos_ini:pos_ini+len_azi] = data_azi |
|
|
588 | 588 | # RADAR |
|
|
589 | 589 | self.res_weather[pos_ini:pos_ini+len_azi,:] = data_weather |
|
|
590 | 590 | else: |
|
|
591 | 591 | # AZIMUTH |
|
|
592 | 592 | self.res_azi[pos_ini:pos_ini+dif] = data_azi[0:dif] |
|
|
593 | 593 | self.res_azi[0:comp] = data_azi[dif:] |
|
|
594 | 594 | # RADAR |
|
|
595 | 595 | self.res_weather[pos_ini:pos_ini+dif,:] = data_weather[0:dif,:] |
|
|
596 | 596 | self.res_weather[0:comp,:] = data_weather[dif:,:] |
|
|
597 | 597 | flag=0 |
|
|
598 | 598 | data_azi = self.res_azi |
|
|
599 | 599 | data_weather = self.res_weather |
|
|
600 | 600 | |
|
|
601 | 601 | return data_weather,data_azi |
|
|
602 | 602 | |
|
|
603 | 603 | def plot(self): |
|
|
604 | 604 | thisDatetime = datetime.datetime.utcfromtimestamp(self.data.times[-1]).strftime('%Y-%m-%d %H:%M:%S') |
|
|
605 | 605 | data = self.data[-1] |
|
|
606 | 606 | r = self.data.yrange |
|
|
607 | 607 | delta_height = r[1]-r[0] |
|
|
608 | 608 | r_mask = numpy.where(r>=0)[0] |
|
|
609 | 609 | r = numpy.arange(len(r_mask))*delta_height |
|
|
610 | 610 | self.y = 2*r |
|
|
611 | 611 | # RADAR |
|
|
612 | 612 | #data_weather = data['weather'] |
|
|
613 | 613 | # PEDESTAL |
|
|
614 | 614 | #data_azi = data['azi'] |
|
|
615 | 615 | res = 1 |
|
|
616 | 616 | # STEP |
|
|
617 | 617 | step = (360/(res*data['weather'].shape[0])) |
|
|
618 | 618 | |
|
|
619 | 619 | self.res_weather, self.res_azi = self.const_ploteo(data_weather=data['weather'][:,r_mask],data_azi=data['azi'],step=step,res=res) |
|
|
620 | 620 | self.res_ele = numpy.mean(data['ele']) |
|
|
621 | 621 | ################# PLOTEO ################### |
|
|
622 | 622 | for i,ax in enumerate(self.axes): |
|
|
623 | 623 | self.zmin = self.zmin if self.zmin else 20 |
|
|
624 | 624 | self.zmax = self.zmax if self.zmax else 80 |
|
|
625 | 625 | if ax.firsttime: |
|
|
626 | 626 | plt.clf() |
|
|
627 | 627 | cgax, pm = wrl.vis.plot_ppi(self.res_weather,r=r,az=self.res_azi,fig=self.figures[0], proj='cg', vmin=self.zmin, vmax=self.zmax) |
|
|
628 | 628 | else: |
|
|
629 | 629 | plt.clf() |
|
|
630 | 630 | cgax, pm = wrl.vis.plot_ppi(self.res_weather,r=r,az=self.res_azi,fig=self.figures[0], proj='cg', vmin=self.zmin, vmax=self.zmax) |
|
|
631 | 631 | caax = cgax.parasites[0] |
|
|
632 | 632 | paax = cgax.parasites[1] |
|
|
633 | 633 | cbar = plt.gcf().colorbar(pm, pad=0.075) |
|
|
634 | 634 | caax.set_xlabel('x_range [km]') |
|
|
635 | 635 | caax.set_ylabel('y_range [km]') |
|
|
636 | 636 | plt.text(1.0, 1.05, 'Azimuth '+str(thisDatetime)+" Step "+str(self.ini)+ " EL: "+str(round(self.res_ele, 1)), transform=caax.transAxes, va='bottom',ha='right') |
|
|
637 | 637 | |
|
|
638 | 638 | self.ini= self.ini+1 |
|
|
639 | 639 | |
|
|
640 | 640 | |
|
|
641 | 641 | class WeatherRHIPlot(Plot): |
|
|
642 | 642 | CODE = 'weather' |
|
|
643 | 643 | plot_name = 'weather' |
|
|
644 | 644 | plot_type = 'rhistyle' |
|
|
645 | 645 | buffering = False |
|
|
646 | 646 | data_ele_tmp = None |
|
|
647 | 647 | |
|
|
648 | 648 | def setup(self): |
|
|
649 | 649 | print("********************") |
|
|
650 | 650 | print("********************") |
|
|
651 | 651 | print("********************") |
|
|
652 | 652 | print("SETUP WEATHER PLOT") |
|
|
653 | 653 | self.ncols = 1 |
|
|
654 | 654 | self.nrows = 1 |
|
|
655 | 655 | self.nplots= 1 |
|
|
656 | 656 | self.ylabel= 'Range [Km]' |
|
|
657 | 657 | self.titles= ['Weather'] |
|
|
658 | 658 | if self.channels is not None: |
|
|
659 | 659 | self.nplots = len(self.channels) |
|
|
660 | 660 | self.nrows = len(self.channels) |
|
|
661 | 661 | else: |
|
|
662 | 662 | self.nplots = self.data.shape(self.CODE)[0] |
|
|
663 | 663 | self.nrows = self.nplots |
|
|
664 | 664 | self.channels = list(range(self.nplots)) |
|
|
665 | 665 | print("channels",self.channels) |
|
|
666 | 666 | print("que saldra", self.data.shape(self.CODE)[0]) |
|
|
667 | 667 | self.titles = ['{} Channel {}'.format(self.CODE.upper(), x) for x in range(self.nrows)] |
|
|
668 | 668 | print("self.titles",self.titles) |
|
|
669 | 669 | self.colorbar=False |
|
|
670 | 670 | self.width =12 |
|
|
671 | 671 | self.height =8 |
|
|
672 | 672 | self.ini =0 |
|
|
673 | 673 | self.len_azi =0 |
|
|
674 | 674 | self.buffer_ini = None |
|
|
675 | 675 | self.buffer_ele = None |
|
|
676 | 676 | self.plots_adjust.update({'wspace': 0.4, 'hspace':0.4, 'left': 0.1, 'right': 0.9, 'bottom': 0.08}) |
|
|
677 | 677 | self.flag =0 |
|
|
678 | 678 | self.indicador= 0 |
|
|
679 | 679 | self.last_data_ele = None |
|
|
680 | 680 | self.val_mean = None |
|
|
681 | 681 | |
|
|
682 | 682 | def update(self, dataOut): |
|
|
683 | 683 | |
|
|
684 | 684 | data = {} |
|
|
685 | 685 | meta = {} |
|
|
686 | 686 | if hasattr(dataOut, 'dataPP_POWER'): |
|
|
687 | 687 | factor = 1 |
|
|
688 | 688 | if hasattr(dataOut, 'nFFTPoints'): |
|
|
689 | 689 | factor = dataOut.normFactor |
|
|
690 | 690 | print("dataOut",dataOut.data_360.shape) |
|
|
691 | 691 | # |
|
|
692 | 692 | data['weather'] = 10*numpy.log10(dataOut.data_360/(factor)) |
|
|
693 | 693 | # |
|
|
694 | 694 | #data['weather'] = 10*numpy.log10(dataOut.data_360[1]/(factor)) |
|
|
695 | 695 | data['azi'] = dataOut.data_azi |
|
|
696 | 696 | data['ele'] = dataOut.data_ele |
|
|
697 | 697 | #print("UPDATE") |
|
|
698 | 698 | #print("data[weather]",data['weather'].shape) |
|
|
699 | 699 | #print("data[azi]",data['azi']) |
|
|
700 | 700 | return data, meta |
|
|
701 | 701 | |
|
|
702 | 702 | def get2List(self,angulos): |
|
|
703 | 703 | list1=[] |
|
|
704 | 704 | list2=[] |
|
|
705 | 705 | for i in reversed(range(len(angulos))): |
|
|
706 | 706 | if not i==0:#el caso de i=0 evalula el primero de la lista con el ultimo y no es relevante |
|
|
707 | 707 | diff_ = angulos[i]-angulos[i-1] |
|
|
708 | 708 | if abs(diff_) >1.5: |
|
|
709 | 709 | list1.append(i-1) |
|
|
710 | 710 | list2.append(diff_) |
|
|
711 | 711 | return list(reversed(list1)),list(reversed(list2)) |
|
|
712 | 712 | |
|
|
713 | 713 | def fixData90(self,list_,ang_): |
|
|
714 | 714 | if list_[0]==-1: |
|
|
715 | 715 | vec = numpy.where(ang_<ang_[0]) |
|
|
716 | 716 | ang_[vec] = ang_[vec]+90 |
|
|
717 | 717 | return ang_ |
|
|
718 | 718 | return ang_ |
|
|
719 | 719 | |
|
|
720 | 720 | def fixData90HL(self,angulos): |
|
|
721 | 721 | vec = numpy.where(angulos>=90) |
|
|
722 | 722 | angulos[vec]=angulos[vec]-90 |
|
|
723 | 723 | return angulos |
|
|
724 | 724 | |
|
|
725 | 725 | |
|
|
726 | 726 | def search_pos(self,pos,list_): |
|
|
727 | 727 | for i in range(len(list_)): |
|
|
728 | 728 | if pos == list_[i]: |
|
|
729 | 729 | return True,i |
|
|
730 | 730 | i=None |
|
|
731 | 731 | return False,i |
|
|
732 | 732 | |
|
|
733 | 733 | def fixDataComp(self,ang_,list1_,list2_,tipo_case): |
|
|
734 | 734 | size = len(ang_) |
|
|
735 | 735 | size2 = 0 |
|
|
736 | 736 | for i in range(len(list2_)): |
|
|
737 | 737 | size2=size2+round(abs(list2_[i]))-1 |
|
|
738 | 738 | new_size= size+size2 |
|
|
739 | 739 | ang_new = numpy.zeros(new_size) |
|
|
740 | 740 | ang_new2 = numpy.zeros(new_size) |
|
|
741 | 741 | |
|
|
742 | 742 | tmp = 0 |
|
|
743 | 743 | c = 0 |
|
|
744 | 744 | for i in range(len(ang_)): |
|
|
745 | 745 | ang_new[tmp +c] = ang_[i] |
|
|
746 | 746 | ang_new2[tmp+c] = ang_[i] |
|
|
747 | 747 | condition , value = self.search_pos(i,list1_) |
|
|
748 | 748 | if condition: |
|
|
749 | 749 | pos = tmp + c + 1 |
|
|
750 | 750 | for k in range(round(abs(list2_[value]))-1): |
|
|
751 | 751 | if tipo_case==0 or tipo_case==3:#subida |
|
|
752 | 752 | ang_new[pos+k] = ang_new[pos+k-1]+1 |
|
|
753 | 753 | ang_new2[pos+k] = numpy.nan |
|
|
754 | 754 | elif tipo_case==1 or tipo_case==2:#bajada |
|
|
755 | 755 | ang_new[pos+k] = ang_new[pos+k-1]-1 |
|
|
756 | 756 | ang_new2[pos+k] = numpy.nan |
|
|
757 | 757 | |
|
|
758 | 758 | tmp = pos +k |
|
|
759 | 759 | c = 0 |
|
|
760 | 760 | c=c+1 |
|
|
761 | 761 | return ang_new,ang_new2 |
|
|
762 | 762 | |
|
|
763 | 763 | def globalCheckPED(self,angulos,tipo_case): |
|
|
764 | 764 | l1,l2 = self.get2List(angulos) |
|
|
765 | 765 | ##print("l1",l1) |
|
|
766 | 766 | ##print("l2",l2) |
|
|
767 | 767 | if len(l1)>0: |
|
|
768 | 768 | #angulos2 = self.fixData90(list_=l1,ang_=angulos) |
|
|
769 | 769 | #l1,l2 = self.get2List(angulos2) |
|
|
770 | 770 | ang1_,ang2_ = self.fixDataComp(ang_=angulos,list1_=l1,list2_=l2,tipo_case=tipo_case) |
|
|
771 | 771 | #ang1_ = self.fixData90HL(ang1_) |
|
|
772 | 772 | #ang2_ = self.fixData90HL(ang2_) |
|
|
773 | 773 | else: |
|
|
774 | 774 | ang1_= angulos |
|
|
775 | 775 | ang2_= angulos |
|
|
776 | 776 | return ang1_,ang2_ |
|
|
777 | 777 | |
|
|
778 | 778 | |
|
|
779 | 779 | def replaceNAN(self,data_weather,data_ele,val): |
|
|
780 | 780 | data= data_ele |
|
|
781 | 781 | data_T= data_weather |
|
|
782 | 782 | if data.shape[0]> data_T.shape[0]: |
|
|
783 | 783 | data_N = numpy.ones( [data.shape[0],data_T.shape[1]]) |
|
|
784 | 784 | c = 0 |
|
|
785 | 785 | for i in range(len(data)): |
|
|
786 | 786 | if numpy.isnan(data[i]): |
|
|
787 | 787 | data_N[i,:]=numpy.ones(data_T.shape[1])*numpy.nan |
|
|
788 | 788 | else: |
|
|
789 | 789 | data_N[i,:]=data_T[c,:] |
|
|
790 | 790 | c=c+1 |
|
|
791 | 791 | return data_N |
|
|
792 | 792 | else: |
|
|
793 | 793 | for i in range(len(data)): |
|
|
794 | 794 | if numpy.isnan(data[i]): |
|
|
795 | 795 | data_T[i,:]=numpy.ones(data_T.shape[1])*numpy.nan |
|
|
796 | 796 | return data_T |
|
|
797 | 797 | |
|
|
798 | 798 | def check_case(self,data_ele,ang_max,ang_min): |
|
|
799 | 799 | start = data_ele[0] |
|
|
800 | 800 | end = data_ele[-1] |
|
|
801 | 801 | number = (end-start) |
|
|
802 | 802 | len_ang=len(data_ele) |
|
|
803 | 803 | print("start",start) |
|
|
804 | 804 | print("end",end) |
|
|
805 | 805 | print("number",number) |
|
|
806 | 806 | |
|
|
807 | 807 | print("len_ang",len_ang) |
|
|
808 | 808 | |
|
|
809 | 809 | #exit(1) |
|
|
810 | 810 | |
|
|
811 | 811 | if start<end and (round(abs(number)+1)>=len_ang or (numpy.argmin(data_ele)==0)):#caso subida |
|
|
812 | 812 | return 0 |
|
|
813 | 813 | #elif start>end and (round(abs(number)+1)>=len_ang or(numpy.argmax(data_ele)==0)):#caso bajada |
|
|
814 | 814 | # return 1 |
|
|
815 | 815 | elif round(abs(number)+1)>=len_ang and (start>end or(numpy.argmax(data_ele)==0)):#caso bajada |
|
|
816 | 816 | return 1 |
|
|
817 | 817 | elif round(abs(number)+1)<len_ang and data_ele[-2]>data_ele[-1]:# caso BAJADA CAMBIO ANG MAX |
|
|
818 | 818 | return 2 |
|
|
819 | 819 | elif round(abs(number)+1)<len_ang and data_ele[-2]<data_ele[-1] :# caso SUBIDA CAMBIO ANG MIN |
|
|
820 | 820 | return 3 |
|
|
821 | 821 | |
|
|
822 | 822 | |
|
|
823 | 823 | def const_ploteo(self,val_ch,data_weather,data_ele,step,res,ang_max,ang_min): |
|
|
824 | 824 | ang_max= ang_max |
|
|
825 | 825 | ang_min= ang_min |
|
|
826 | 826 | data_weather=data_weather |
|
|
827 | 827 | val_ch=val_ch |
|
|
828 | 828 | ##print("*********************DATA WEATHER**************************************") |
|
|
829 | 829 | ##print(data_weather) |
|
|
830 | 830 | if self.ini==0: |
|
|
831 | 831 | ''' |
|
|
832 | 832 | print("**********************************************") |
|
|
833 | 833 | print("**********************************************") |
|
|
834 | 834 | print("***************ini**************") |
|
|
835 | 835 | print("**********************************************") |
|
|
836 | 836 | print("**********************************************") |
|
|
837 | 837 | ''' |
|
|
838 | 838 | #print("data_ele",data_ele) |
|
|
839 | 839 | #---------------------------------------------------------- |
|
|
840 | 840 | tipo_case = self.check_case(data_ele,ang_max,ang_min) |
|
|
841 | 841 | print("check_case",tipo_case) |
|
|
842 | 842 | #exit(1) |
|
|
843 | 843 | #--------------------- new ------------------------- |
|
|
844 | 844 | data_ele_new ,data_ele_old= self.globalCheckPED(data_ele,tipo_case) |
|
|
845 | 845 | |
|
|
846 | 846 | #-------------------------CAMBIOS RHI--------------------------------- |
|
|
847 | 847 | start= ang_min |
|
|
848 | 848 | end = ang_max |
|
|
849 | 849 | n= (ang_max-ang_min)/res |
|
|
850 | 850 | #------ new |
|
|
851 | 851 | self.start_data_ele = data_ele_new[0] |
|
|
852 | 852 | self.end_data_ele = data_ele_new[-1] |
|
|
853 | 853 | if tipo_case==0 or tipo_case==3: # SUBIDA |
|
|
854 | 854 | n1= round(self.start_data_ele)- start |
|
|
855 | 855 | n2= end - round(self.end_data_ele) |
|
|
856 | 856 | print(self.start_data_ele) |
|
|
857 | 857 | print(self.end_data_ele) |
|
|
858 | 858 | if n1>0: |
|
|
859 | 859 | ele1= numpy.linspace(ang_min+1,self.start_data_ele-1,n1) |
|
|
860 | 860 | ele1_nan= numpy.ones(n1)*numpy.nan |
|
|
861 | 861 | data_ele = numpy.hstack((ele1,data_ele_new)) |
|
|
862 | 862 | print("ele1_nan",ele1_nan.shape) |
|
|
863 | 863 | print("data_ele_old",data_ele_old.shape) |
|
|
864 | 864 | data_ele_old = numpy.hstack((ele1_nan,data_ele_old)) |
|
|
865 | 865 | if n2>0: |
|
|
866 | 866 | ele2= numpy.linspace(self.end_data_ele+1,end,n2) |
|
|
867 | 867 | ele2_nan= numpy.ones(n2)*numpy.nan |
|
|
868 | 868 | data_ele = numpy.hstack((data_ele,ele2)) |
|
|
869 | 869 | print("ele2_nan",ele2_nan.shape) |
|
|
870 | 870 | print("data_ele_old",data_ele_old.shape) |
|
|
871 | 871 | data_ele_old = numpy.hstack((data_ele_old,ele2_nan)) |
|
|
872 | 872 | |
|
|
873 | 873 | if tipo_case==1 or tipo_case==2: # BAJADA |
|
|
874 | 874 | data_ele_new = data_ele_new[::-1] # reversa |
|
|
875 | 875 | data_ele_old = data_ele_old[::-1]# reversa |
|
|
876 | 876 | data_weather = data_weather[::-1,:]# reversa |
|
|
877 | 877 | vec= numpy.where(data_ele_new<ang_max) |
|
|
878 | 878 | data_ele_new = data_ele_new[vec] |
|
|
879 | 879 | data_ele_old = data_ele_old[vec] |
|
|
880 | 880 | data_weather = data_weather[vec[0]] |
|
|
881 | 881 | vec2= numpy.where(0<data_ele_new) |
|
|
882 | 882 | data_ele_new = data_ele_new[vec2] |
|
|
883 | 883 | data_ele_old = data_ele_old[vec2] |
|
|
884 | 884 | data_weather = data_weather[vec2[0]] |
|
|
885 | 885 | self.start_data_ele = data_ele_new[0] |
|
|
886 | 886 | self.end_data_ele = data_ele_new[-1] |
|
|
887 | 887 | |
|
|
888 | 888 | n1= round(self.start_data_ele)- start |
|
|
889 | 889 | n2= end - round(self.end_data_ele)-1 |
|
|
890 | 890 | print(self.start_data_ele) |
|
|
891 | 891 | print(self.end_data_ele) |
|
|
892 | 892 | if n1>0: |
|
|
893 | 893 | ele1= numpy.linspace(ang_min+1,self.start_data_ele-1,n1) |
|
|
894 | 894 | ele1_nan= numpy.ones(n1)*numpy.nan |
|
|
895 | 895 | data_ele = numpy.hstack((ele1,data_ele_new)) |
|
|
896 | 896 | data_ele_old = numpy.hstack((ele1_nan,data_ele_old)) |
|
|
897 | 897 | if n2>0: |
|
|
898 | 898 | ele2= numpy.linspace(self.end_data_ele+1,end,n2) |
|
|
899 | 899 | ele2_nan= numpy.ones(n2)*numpy.nan |
|
|
900 | 900 | data_ele = numpy.hstack((data_ele,ele2)) |
|
|
901 | 901 | data_ele_old = numpy.hstack((data_ele_old,ele2_nan)) |
|
|
902 | 902 | # RADAR |
|
|
903 | 903 | # NOTA data_ele y data_weather es la variable que retorna |
|
|
904 | 904 | val_mean = numpy.mean(data_weather[:,-1]) |
|
|
905 | 905 | self.val_mean = val_mean |
|
|
906 | 906 | data_weather = self.replaceNAN(data_weather=data_weather,data_ele=data_ele_old,val=self.val_mean) |
|
|
907 | 907 | self.data_ele_tmp[val_ch]= data_ele_old |
|
|
908 | 908 | else: |
|
|
909 | 909 | #print("**********************************************") |
|
|
910 | 910 | #print("****************VARIABLE**********************") |
|
|
911 | 911 | #-------------------------CAMBIOS RHI--------------------------------- |
|
|
912 | 912 | #--------------------------------------------------------------------- |
|
|
913 | 913 | ##print("INPUT data_ele",data_ele) |
|
|
914 | 914 | flag=0 |
|
|
915 | 915 | start_ele = self.res_ele[0] |
|
|
916 | 916 | tipo_case = self.check_case(data_ele,ang_max,ang_min) |
|
|
917 | 917 | #print("TIPO DE DATA",tipo_case) |
|
|
918 | 918 | #-----------new------------ |
|
|
919 | 919 | data_ele ,data_ele_old = self.globalCheckPED(data_ele,tipo_case) |
|
|
920 | 920 | data_weather = self.replaceNAN(data_weather=data_weather,data_ele=data_ele_old,val=self.val_mean) |
|
|
921 | 921 | |
|
|
922 | 922 | #-------------------------------NEW RHI ITERATIVO------------------------- |
|
|
923 | 923 | |
|
|
924 | 924 | if tipo_case==0 : # SUBIDA |
|
|
925 | 925 | vec = numpy.where(data_ele<ang_max) |
|
|
926 | 926 | data_ele = data_ele[vec] |
|
|
927 | 927 | data_ele_old = data_ele_old[vec] |
|
|
928 | 928 | data_weather = data_weather[vec[0]] |
|
|
929 | 929 | |
|
|
930 | 930 | vec2 = numpy.where(0<data_ele) |
|
|
931 | 931 | data_ele= data_ele[vec2] |
|
|
932 | 932 | data_ele_old= data_ele_old[vec2] |
|
|
933 | 933 | ##print(data_ele_new) |
|
|
934 | 934 | data_weather= data_weather[vec2[0]] |
|
|
935 | 935 | |
|
|
936 | 936 | new_i_ele = int(round(data_ele[0])) |
|
|
937 | 937 | new_f_ele = int(round(data_ele[-1])) |
|
|
938 | 938 | #print(new_i_ele) |
|
|
939 | 939 | #print(new_f_ele) |
|
|
940 | 940 | #print(data_ele,len(data_ele)) |
|
|
941 | 941 | #print(data_ele_old,len(data_ele_old)) |
|
|
942 | 942 | if new_i_ele< 2: |
|
|
943 | 943 | self.data_ele_tmp[val_ch] = numpy.ones(ang_max-ang_min)*numpy.nan |
|
|
944 | 944 | self.res_weather[val_ch] = self.replaceNAN(data_weather=self.res_weather[val_ch],data_ele=self.data_ele_tmp[val_ch],val=self.val_mean) |
|
|
945 | 945 | self.data_ele_tmp[val_ch][new_i_ele:new_i_ele+len(data_ele)]=data_ele_old |
|
|
946 | 946 | self.res_ele[new_i_ele:new_i_ele+len(data_ele)]= data_ele |
|
|
947 | 947 | self.res_weather[val_ch][new_i_ele:new_i_ele+len(data_ele),:]= data_weather |
|
|
948 | 948 | data_ele = self.res_ele |
|
|
949 | 949 | data_weather = self.res_weather[val_ch] |
|
|
950 | 950 | |
|
|
951 | 951 | elif tipo_case==1 : #BAJADA |
|
|
952 | 952 | data_ele = data_ele[::-1] # reversa |
|
|
953 | 953 | data_ele_old = data_ele_old[::-1]# reversa |
|
|
954 | 954 | data_weather = data_weather[::-1,:]# reversa |
|
|
955 | 955 | vec= numpy.where(data_ele<ang_max) |
|
|
956 | 956 | data_ele = data_ele[vec] |
|
|
957 | 957 | data_ele_old = data_ele_old[vec] |
|
|
958 | 958 | data_weather = data_weather[vec[0]] |
|
|
959 | 959 | vec2= numpy.where(0<data_ele) |
|
|
960 | 960 | data_ele = data_ele[vec2] |
|
|
961 | 961 | data_ele_old = data_ele_old[vec2] |
|
|
962 | 962 | data_weather = data_weather[vec2[0]] |
|
|
963 | 963 | |
|
|
964 | 964 | |
|
|
965 | 965 | new_i_ele = int(round(data_ele[0])) |
|
|
966 | 966 | new_f_ele = int(round(data_ele[-1])) |
|
|
967 | 967 | #print(data_ele) |
|
|
968 | 968 | #print(ang_max) |
|
|
969 | 969 | #print(data_ele_old) |
|
|
970 | 970 | if new_i_ele <= 1: |
|
|
971 | 971 | new_i_ele = 1 |
|
|
972 | 972 | if round(data_ele[-1])>=ang_max-1: |
|
|
973 | 973 | self.data_ele_tmp[val_ch] = numpy.ones(ang_max-ang_min)*numpy.nan |
|
|
974 | 974 | self.res_weather[val_ch] = self.replaceNAN(data_weather=self.res_weather[val_ch],data_ele=self.data_ele_tmp[val_ch],val=self.val_mean) |
|
|
975 | 975 | self.data_ele_tmp[val_ch][new_i_ele-1:new_i_ele+len(data_ele)-1]=data_ele_old |
|
|
976 | 976 | self.res_ele[new_i_ele-1:new_i_ele+len(data_ele)-1]= data_ele |
|
|
977 | 977 | self.res_weather[val_ch][new_i_ele-1:new_i_ele+len(data_ele)-1,:]= data_weather |
|
|
978 | 978 | data_ele = self.res_ele |
|
|
979 | 979 | data_weather = self.res_weather[val_ch] |
|
|
980 | 980 | |
|
|
981 | 981 | elif tipo_case==2: #bajada |
|
|
982 | 982 | vec = numpy.where(data_ele<ang_max) |
|
|
983 | 983 | data_ele = data_ele[vec] |
|
|
984 | 984 | data_weather= data_weather[vec[0]] |
|
|
985 | 985 | |
|
|
986 | 986 | len_vec = len(vec) |
|
|
987 | 987 | data_ele_new = data_ele[::-1] # reversa |
|
|
988 | 988 | data_weather = data_weather[::-1,:] |
|
|
989 | 989 | new_i_ele = int(data_ele_new[0]) |
|
|
990 | 990 | new_f_ele = int(data_ele_new[-1]) |
|
|
991 | 991 | |
|
|
992 | 992 | n1= new_i_ele- ang_min |
|
|
993 | 993 | n2= ang_max - new_f_ele-1 |
|
|
994 | 994 | if n1>0: |
|
|
995 | 995 | ele1= numpy.linspace(ang_min+1,new_i_ele-1,n1) |
|
|
996 | 996 | ele1_nan= numpy.ones(n1)*numpy.nan |
|
|
997 | 997 | data_ele = numpy.hstack((ele1,data_ele_new)) |
|
|
998 | 998 | data_ele_old = numpy.hstack((ele1_nan,data_ele_new)) |
|
|
999 | 999 | if n2>0: |
|
|
1000 | 1000 | ele2= numpy.linspace(new_f_ele+1,ang_max,n2) |
|
|
1001 | 1001 | ele2_nan= numpy.ones(n2)*numpy.nan |
|
|
1002 | 1002 | data_ele = numpy.hstack((data_ele,ele2)) |
|
|
1003 | 1003 | data_ele_old = numpy.hstack((data_ele_old,ele2_nan)) |
|
|
1004 | 1004 | |
|
|
1005 | 1005 | self.data_ele_tmp[val_ch] = data_ele_old |
|
|
1006 | 1006 | self.res_ele = data_ele |
|
|
1007 | 1007 | self.res_weather[val_ch] = self.replaceNAN(data_weather=data_weather,data_ele=data_ele_old,val=self.val_mean) |
|
|
1008 | 1008 | data_ele = self.res_ele |
|
|
1009 | 1009 | data_weather = self.res_weather[val_ch] |
|
|
1010 | 1010 | |
|
|
1011 | 1011 | elif tipo_case==3:#subida |
|
|
1012 | 1012 | vec = numpy.where(0<data_ele) |
|
|
1013 | 1013 | data_ele= data_ele[vec] |
|
|
1014 | 1014 | data_ele_new = data_ele |
|
|
1015 | 1015 | data_ele_old= data_ele_old[vec] |
|
|
1016 | 1016 | data_weather= data_weather[vec[0]] |
|
|
1017 | 1017 | pos_ini = numpy.argmin(data_ele) |
|
|
1018 | 1018 | if pos_ini>0: |
|
|
1019 | 1019 | len_vec= len(data_ele) |
|
|
1020 | 1020 | vec3 = numpy.linspace(pos_ini,len_vec-1,len_vec-pos_ini).astype(int) |
|
|
1021 | 1021 | #print(vec3) |
|
|
1022 | 1022 | data_ele= data_ele[vec3] |
|
|
1023 | 1023 | data_ele_new = data_ele |
|
|
1024 | 1024 | data_ele_old= data_ele_old[vec3] |
|
|
1025 | 1025 | data_weather= data_weather[vec3] |
|
|
1026 | 1026 | |
|
|
1027 | 1027 | new_i_ele = int(data_ele_new[0]) |
|
|
1028 | 1028 | new_f_ele = int(data_ele_new[-1]) |
|
|
1029 | 1029 | n1= new_i_ele- ang_min |
|
|
1030 | 1030 | n2= ang_max - new_f_ele-1 |
|
|
1031 | 1031 | if n1>0: |
|
|
1032 | 1032 | ele1= numpy.linspace(ang_min+1,new_i_ele-1,n1) |
|
|
1033 | 1033 | ele1_nan= numpy.ones(n1)*numpy.nan |
|
|
1034 | 1034 | data_ele = numpy.hstack((ele1,data_ele_new)) |
|
|
1035 | 1035 | data_ele_old = numpy.hstack((ele1_nan,data_ele_new)) |
|
|
1036 | 1036 | if n2>0: |
|
|
1037 | 1037 | ele2= numpy.linspace(new_f_ele+1,ang_max,n2) |
|
|
1038 | 1038 | ele2_nan= numpy.ones(n2)*numpy.nan |
|
|
1039 | 1039 | data_ele = numpy.hstack((data_ele,ele2)) |
|
|
1040 | 1040 | data_ele_old = numpy.hstack((data_ele_old,ele2_nan)) |
|
|
1041 | 1041 | |
|
|
1042 | 1042 | self.data_ele_tmp[val_ch] = data_ele_old |
|
|
1043 | 1043 | self.res_ele = data_ele |
|
|
1044 | 1044 | self.res_weather[val_ch] = self.replaceNAN(data_weather=data_weather,data_ele=data_ele_old,val=self.val_mean) |
|
|
1045 | 1045 | data_ele = self.res_ele |
|
|
1046 | 1046 | data_weather = self.res_weather[val_ch] |
|
|
1047 | 1047 | #print("self.data_ele_tmp",self.data_ele_tmp) |
|
|
1048 | 1048 | return data_weather,data_ele |
|
|
1049 | 1049 | |
|
|
1050 | 1050 | |
|
|
1051 | 1051 | def plot(self): |
|
|
1052 | 1052 | thisDatetime = datetime.datetime.utcfromtimestamp(self.data.times[-1]).strftime('%Y-%m-%d %H:%M:%S') |
|
|
1053 | 1053 | data = self.data[-1] |
|
|
1054 | 1054 | r = self.data.yrange |
|
|
1055 | 1055 | delta_height = r[1]-r[0] |
|
|
1056 | 1056 | r_mask = numpy.where(r>=0)[0] |
|
|
1057 | 1057 | ##print("delta_height",delta_height) |
|
|
1058 | 1058 | #print("r_mask",r_mask,len(r_mask)) |
|
|
1059 | 1059 | r = numpy.arange(len(r_mask))*delta_height |
|
|
1060 | 1060 | self.y = 2*r |
|
|
1061 | 1061 | res = 1 |
|
|
1062 | 1062 | ###print("data['weather'].shape[0]",data['weather'].shape[0]) |
|
|
1063 | 1063 | ang_max = self.ang_max |
|
|
1064 | 1064 | ang_min = self.ang_min |
|
|
1065 | 1065 | var_ang =ang_max - ang_min |
|
|
1066 | 1066 | step = (int(var_ang)/(res*data['weather'].shape[0])) |
|
|
1067 | 1067 | ###print("step",step) |
|
|
1068 | 1068 | #-------------------------------------------------------- |
|
|
1069 | 1069 | ##print('weather',data['weather'].shape) |
|
|
1070 | 1070 | ##print('ele',data['ele'].shape) |
|
|
1071 | 1071 | |
|
|
1072 | 1072 | ###self.res_weather, self.res_ele = self.const_ploteo(data_weather=data['weather'][:,r_mask],data_ele=data['ele'],step=step,res=res,ang_max=ang_max,ang_min=ang_min) |
|
|
1073 | 1073 | ###self.res_azi = numpy.mean(data['azi']) |
|
|
1074 | 1074 | ###print("self.res_ele",self.res_ele) |
|
|
1075 | 1075 | plt.clf() |
|
|
1076 | 1076 | subplots = [121, 122] |
|
|
1077 | 1077 | cg={'angular_spacing': 20.} |
|
|
1078 | 1078 | if self.ini==0: |
|
|
1079 | 1079 | self.data_ele_tmp = numpy.ones([self.nplots,int(var_ang)])*numpy.nan |
|
|
1080 | 1080 | self.res_weather= numpy.ones([self.nplots,int(var_ang),len(r_mask)])*numpy.nan |
|
|
1081 | 1081 | print("SHAPE",self.data_ele_tmp.shape) |
|
|
1082 | 1082 | |
|
|
1083 | 1083 | for i,ax in enumerate(self.axes): |
|
|
1084 | 1084 | self.res_weather[i], self.res_ele = self.const_ploteo(val_ch=i, data_weather=data['weather'][i][:,r_mask],data_ele=data['ele'],step=step,res=res,ang_max=ang_max,ang_min=ang_min) |
|
|
1085 | 1085 | self.res_azi = numpy.mean(data['azi']) |
|
|
1086 | 1086 | if i==0: |
|
|
1087 | 1087 | print("*****************************************************************************to plot**************************",self.res_weather[i].shape) |
|
|
1088 | 1088 | self.zmin = self.zmin if self.zmin else 20 |
|
|
1089 | 1089 | self.zmax = self.zmax if self.zmax else 80 |
|
|
1090 | 1090 | if ax.firsttime: |
|
|
1091 | 1091 | #plt.clf() |
|
|
1092 | 1092 | cgax, pm = wrl.vis.plot_rhi(self.res_weather[i],r=r,th=self.res_ele,ax=subplots[i], proj=cg,vmin=self.zmin, vmax=self.zmax) |
|
|
1093 | 1093 | #fig=self.figures[0] |
|
|
1094 | 1094 | else: |
|
|
1095 | 1095 | #plt.clf() |
|
|
1096 | 1096 | if i==0: |
|
|
1097 | 1097 | print(self.res_weather[i]) |
|
|
1098 | 1098 | print(self.res_ele) |
|
|
1099 | 1099 | cgax, pm = wrl.vis.plot_rhi(self.res_weather[i],r=r,th=self.res_ele,ax=subplots[i], proj=cg,vmin=self.zmin, vmax=self.zmax) |
|
|
1100 | 1100 | caax = cgax.parasites[0] |
|
|
1101 | 1101 | paax = cgax.parasites[1] |
|
|
1102 | 1102 | cbar = plt.gcf().colorbar(pm, pad=0.075) |
|
|
1103 | 1103 | caax.set_xlabel('x_range [km]') |
|
|
1104 | 1104 | caax.set_ylabel('y_range [km]') |
|
|
1105 | 1105 | plt.text(1.0, 1.05, 'Elevacion '+str(thisDatetime)+" Step "+str(self.ini)+ " Azi: "+str(round(self.res_azi,2)), transform=caax.transAxes, va='bottom',ha='right') |
|
|
1106 | 1106 | print("***************************self.ini****************************",self.ini) |
|
|
1107 | 1107 | self.ini= self.ini+1 |
|
|
1108 | 1108 | |
|
|
1109 | 1109 | class Weather_vRF_Plot(Plot): |
|
|
1110 | 1110 | CODE = 'PPI' |
|
|
1111 | 1111 | plot_name = 'PPI' |
|
|
1112 | 1112 | #plot_type = 'ppistyle' |
|
|
1113 | 1113 | buffering = False |
|
|
1114 | 1114 | |
|
|
1115 | 1115 | def setup(self): |
|
|
1116 | 1116 | |
|
|
1117 | 1117 | self.ncols = 1 |
|
|
1118 | 1118 | self.nrows = 1 |
|
|
1119 | 1119 | self.width =8 |
|
|
1120 | 1120 | self.height =8 |
|
|
1121 | 1121 | self.nplots= 1 |
|
|
1122 | 1122 | self.ylabel= 'Range [Km]' |
|
|
1123 | 1123 | self.xlabel= 'Range [Km]' |
|
|
1124 | 1124 | self.titles= ['PPI'] |
|
|
1125 | 1125 | self.polar = True |
|
|
1126 | 1126 | if self.channels is not None: |
|
|
1127 | 1127 | self.nplots = len(self.channels) |
|
|
1128 | 1128 | self.nrows = len(self.channels) |
|
|
1129 | 1129 | else: |
|
|
1130 | 1130 | self.nplots = self.data.shape(self.CODE)[0] |
|
|
1131 | 1131 | self.nrows = self.nplots |
|
|
1132 | 1132 | self.channels = list(range(self.nplots)) |
|
|
1133 | 1133 | |
|
|
1134 | 1134 | if self.CODE == 'POWER': |
|
|
1135 | 1135 | self.cb_label = r'Power (dB)' |
|
|
1136 | 1136 | elif self.CODE == 'DOPPLER': |
|
|
1137 | 1137 | self.cb_label = r'Velocity (m/s)' |
|
|
1138 | 1138 | self.colorbar=True |
|
|
1139 | 1139 | self.width = 9 |
|
|
1140 | 1140 | self.height =8 |
|
|
1141 | 1141 | self.ini =0 |
|
|
1142 | 1142 | self.len_azi =0 |
|
|
1143 | 1143 | self.buffer_ini = None |
|
|
1144 | 1144 | self.buffer_ele = None |
|
|
1145 | 1145 | self.plots_adjust.update({'wspace': 0.4, 'hspace':0.4, 'left': 0.15, 'right': 0.9, 'bottom': 0.08}) |
|
|
1146 | 1146 | self.flag =0 |
|
|
1147 | 1147 | self.indicador= 0 |
|
|
1148 | 1148 | self.last_data_ele = None |
|
|
1149 | 1149 | self.val_mean = None |
|
|
1150 | 1150 | |
|
|
1151 | 1151 | def update(self, dataOut): |
|
|
1152 | 1152 | |
|
|
1153 | 1153 | data = {} |
|
|
1154 | 1154 | meta = {} |
|
|
1155 | 1155 | if hasattr(dataOut, 'dataPP_POWER'): |
|
|
1156 | 1156 | factor = 1 |
|
|
1157 | 1157 | if hasattr(dataOut, 'nFFTPoints'): |
|
|
1158 | 1158 | factor = dataOut.normFactor |
|
|
1159 | 1159 | |
|
|
1160 | 1160 | if 'pow' in self.attr_data[0].lower(): |
|
|
1161 | 1161 | data['data'] = 10*numpy.log10(getattr(dataOut, self.attr_data[0])/(factor)) |
|
|
1162 | 1162 | else: |
|
|
1163 | 1163 | data['data'] = getattr(dataOut, self.attr_data[0])/(factor) |
|
|
1164 | 1164 | |
|
|
1165 | 1165 | data['azi'] = dataOut.data_azi |
|
|
1166 | 1166 | data['ele'] = dataOut.data_ele |
|
|
1167 | 1167 | |
|
|
1168 | 1168 | return data, meta |
|
|
1169 | 1169 | |
|
|
1170 | 1170 | def plot(self): |
|
|
1171 | 1171 | data = self.data[-1] |
|
|
1172 | 1172 | r = self.data.yrange |
|
|
1173 | 1173 | delta_height = r[1]-r[0] |
|
|
1174 | 1174 | r_mask = numpy.where(r>=0)[0] |
|
|
1175 | 1175 | self.r_mask = r_mask |
|
|
1176 | 1176 | r = numpy.arange(len(r_mask))*delta_height |
|
|
1177 | 1177 | self.y = 2*r |
|
|
1178 | 1178 | |
|
|
1179 | 1179 | z = data['data'][self.channels[0]][:,r_mask] |
|
|
1180 | 1180 | |
|
|
1181 | 1181 | self.titles = [] |
|
|
1182 | 1182 | |
|
|
1183 | 1183 | self.ymax = self.ymax if self.ymax else numpy.nanmax(r) |
|
|
1184 | 1184 | self.ymin = self.ymin if self.ymin else numpy.nanmin(r) |
|
|
1185 | 1185 | self.zmax = self.zmax if self.zmax else numpy.nanmax(z) |
|
|
1186 | 1186 | self.zmin = self.zmin if self.zmin else numpy.nanmin(z) |
|
|
1187 | 1187 | self.ang_min = self.ang_min if self.ang_min else 0 |
|
|
1188 | 1188 | self.ang_max = self.ang_max if self.ang_max else 360 |
|
|
1189 | 1189 | |
|
|
1190 | 1190 | r, theta = numpy.meshgrid(r, numpy.radians(data['azi']) ) |
|
|
1191 | 1191 | |
|
|
1192 | 1192 | for i,ax in enumerate(self.axes): |
|
|
1193 | 1193 | |
|
|
1194 | 1194 | if ax.firsttime: |
|
|
1195 | 1195 | ax.set_xlim(numpy.radians(self.ang_min),numpy.radians(self.ang_max)) |
|
|
1196 | 1196 | ax.plt = ax.pcolormesh(theta, r, z, cmap=self.colormap, vmin=self.zmin, vmax=self.zmax) |
|
|
1197 | 1197 | |
|
|
1198 | 1198 | else: |
|
|
1199 | 1199 | ax.set_xlim(numpy.radians(self.ang_min),numpy.radians(self.ang_max)) |
|
|
1200 | 1200 | ax.plt = ax.pcolormesh(theta, r, z, cmap=self.colormap, vmin=self.zmin, vmax=self.zmax) |
|
|
1201 | ||
|
|
1201 | ||
|
|
1202 | 1202 | ax.grid(True) |
|
|
1203 | ||
|
|
1203 | ||
|
|
1204 | 1204 | if len(self.channels) !=1: |
|
|
1205 | 1205 | self.titles = ['PPI {} at EL: {} Channel {}'.format(self.self.labels[x], str(round(numpy.mean(data['ele']),1)), x) for x in range(self.nrows)] |
|
|
1206 | 1206 | else: |
|
|
1207 | 1207 | self.titles = ['PPI {} at EL: {} Channel {}'.format(self.labels[0], str(round(numpy.mean(data['ele']),1)), self.channels[0])] |
|
|
1208 | 1208 | |
|
|
1209 | 1209 | class WeatherRHI_vRF2_Plot(Plot): |
|
|
1210 | 1210 | CODE = 'weather' |
|
|
1211 | 1211 | plot_name = 'weather' |
|
|
1212 | 1212 | plot_type = 'rhistyle' |
|
|
1213 | 1213 | buffering = False |
|
|
1214 | 1214 | data_ele_tmp = None |
|
|
1215 | 1215 | |
|
|
1216 | 1216 | def setup(self): |
|
|
1217 | 1217 | print("********************") |
|
|
1218 | 1218 | print("********************") |
|
|
1219 | 1219 | print("********************") |
|
|
1220 | 1220 | print("SETUP WEATHER PLOT") |
|
|
1221 | 1221 | self.ncols = 1 |
|
|
1222 | 1222 | self.nrows = 1 |
|
|
1223 | 1223 | self.nplots= 1 |
|
|
1224 | 1224 | self.ylabel= 'Range [Km]' |
|
|
1225 | 1225 | self.titles= ['Weather'] |
|
|
1226 | 1226 | if self.channels is not None: |
|
|
1227 | 1227 | self.nplots = len(self.channels) |
|
|
1228 | 1228 | self.nrows = len(self.channels) |
|
|
1229 | 1229 | else: |
|
|
1230 | 1230 | self.nplots = self.data.shape(self.CODE)[0] |
|
|
1231 | 1231 | self.nrows = self.nplots |
|
|
1232 | 1232 | self.channels = list(range(self.nplots)) |
|
|
1233 | 1233 | print("channels",self.channels) |
|
|
1234 | 1234 | print("que saldra", self.data.shape(self.CODE)[0]) |
|
|
1235 | 1235 | self.titles = ['{} Channel {}'.format(self.CODE.upper(), x) for x in range(self.nrows)] |
|
|
1236 | 1236 | print("self.titles",self.titles) |
|
|
1237 | 1237 | self.colorbar=False |
|
|
1238 | 1238 | self.width =8 |
|
|
1239 | 1239 | self.height =8 |
|
|
1240 | 1240 | self.ini =0 |
|
|
1241 | 1241 | self.len_azi =0 |
|
|
1242 | 1242 | self.buffer_ini = None |
|
|
1243 | 1243 | self.buffer_ele = None |
|
|
1244 | 1244 | self.plots_adjust.update({'wspace': 0.4, 'hspace':0.4, 'left': 0.1, 'right': 0.9, 'bottom': 0.08}) |
|
|
1245 | 1245 | self.flag =0 |
|
|
1246 | 1246 | self.indicador= 0 |
|
|
1247 | 1247 | self.last_data_ele = None |
|
|
1248 | 1248 | self.val_mean = None |
|
|
1249 | 1249 | |
|
|
1250 | 1250 | def update(self, dataOut): |
|
|
1251 | 1251 | |
|
|
1252 | 1252 | data = {} |
|
|
1253 | 1253 | meta = {} |
|
|
1254 | 1254 | if hasattr(dataOut, 'dataPP_POWER'): |
|
|
1255 | 1255 | factor = 1 |
|
|
1256 | 1256 | if hasattr(dataOut, 'nFFTPoints'): |
|
|
1257 | 1257 | factor = dataOut.normFactor |
|
|
1258 | 1258 | print("dataOut",dataOut.data_360.shape) |
|
|
1259 | 1259 | # |
|
|
1260 | 1260 | data['weather'] = 10*numpy.log10(dataOut.data_360/(factor)) |
|
|
1261 | 1261 | # |
|
|
1262 | 1262 | #data['weather'] = 10*numpy.log10(dataOut.data_360[1]/(factor)) |
|
|
1263 | 1263 | data['azi'] = dataOut.data_azi |
|
|
1264 | 1264 | data['ele'] = dataOut.data_ele |
|
|
1265 | 1265 | data['case_flag'] = dataOut.case_flag |
|
|
1266 | 1266 | #print("UPDATE") |
|
|
1267 | 1267 | #print("data[weather]",data['weather'].shape) |
|
|
1268 | 1268 | #print("data[azi]",data['azi']) |
|
|
1269 | 1269 | return data, meta |
|
|
1270 | 1270 | |
|
|
1271 | 1271 | def get2List(self,angulos): |
|
|
1272 | 1272 | list1=[] |
|
|
1273 | 1273 | list2=[] |
|
|
1274 | 1274 | for i in reversed(range(len(angulos))): |
|
|
1275 | 1275 | if not i==0:#el caso de i=0 evalula el primero de la lista con el ultimo y no es relevante |
|
|
1276 | 1276 | diff_ = angulos[i]-angulos[i-1] |
|
|
1277 | 1277 | if abs(diff_) >1.5: |
|
|
1278 | 1278 | list1.append(i-1) |
|
|
1279 | 1279 | list2.append(diff_) |
|
|
1280 | 1280 | return list(reversed(list1)),list(reversed(list2)) |
|
|
1281 | 1281 | |
|
|
1282 | 1282 | def fixData90(self,list_,ang_): |
|
|
1283 | 1283 | if list_[0]==-1: |
|
|
1284 | 1284 | vec = numpy.where(ang_<ang_[0]) |
|
|
1285 | 1285 | ang_[vec] = ang_[vec]+90 |
|
|
1286 | 1286 | return ang_ |
|
|
1287 | 1287 | return ang_ |
|
|
1288 | 1288 | |
|
|
1289 | 1289 | def fixData90HL(self,angulos): |
|
|
1290 | 1290 | vec = numpy.where(angulos>=90) |
|
|
1291 | 1291 | angulos[vec]=angulos[vec]-90 |
|
|
1292 | 1292 | return angulos |
|
|
1293 | 1293 | |
|
|
1294 | 1294 | |
|
|
1295 | 1295 | def search_pos(self,pos,list_): |
|
|
1296 | 1296 | for i in range(len(list_)): |
|
|
1297 | 1297 | if pos == list_[i]: |
|
|
1298 | 1298 | return True,i |
|
|
1299 | 1299 | i=None |
|
|
1300 | 1300 | return False,i |
|
|
1301 | 1301 | |
|
|
1302 | 1302 | def fixDataComp(self,ang_,list1_,list2_,tipo_case): |
|
|
1303 | 1303 | size = len(ang_) |
|
|
1304 | 1304 | size2 = 0 |
|
|
1305 | 1305 | for i in range(len(list2_)): |
|
|
1306 | 1306 | size2=size2+round(abs(list2_[i]))-1 |
|
|
1307 | 1307 | new_size= size+size2 |
|
|
1308 | 1308 | ang_new = numpy.zeros(new_size) |
|
|
1309 | 1309 | ang_new2 = numpy.zeros(new_size) |
|
|
1310 | 1310 | |
|
|
1311 | 1311 | tmp = 0 |
|
|
1312 | 1312 | c = 0 |
|
|
1313 | 1313 | for i in range(len(ang_)): |
|
|
1314 | 1314 | ang_new[tmp +c] = ang_[i] |
|
|
1315 | 1315 | ang_new2[tmp+c] = ang_[i] |
|
|
1316 | 1316 | condition , value = self.search_pos(i,list1_) |
|
|
1317 | 1317 | if condition: |
|
|
1318 | 1318 | pos = tmp + c + 1 |
|
|
1319 | 1319 | for k in range(round(abs(list2_[value]))-1): |
|
|
1320 | 1320 | if tipo_case==0 or tipo_case==3:#subida |
|
|
1321 | 1321 | ang_new[pos+k] = ang_new[pos+k-1]+1 |
|
|
1322 | 1322 | ang_new2[pos+k] = numpy.nan |
|
|
1323 | 1323 | elif tipo_case==1 or tipo_case==2:#bajada |
|
|
1324 | 1324 | ang_new[pos+k] = ang_new[pos+k-1]-1 |
|
|
1325 | 1325 | ang_new2[pos+k] = numpy.nan |
|
|
1326 | 1326 | |
|
|
1327 | 1327 | tmp = pos +k |
|
|
1328 | 1328 | c = 0 |
|
|
1329 | 1329 | c=c+1 |
|
|
1330 | 1330 | return ang_new,ang_new2 |
|
|
1331 | 1331 | |
|
|
1332 | 1332 | def globalCheckPED(self,angulos,tipo_case): |
|
|
1333 | 1333 | l1,l2 = self.get2List(angulos) |
|
|
1334 | 1334 | ##print("l1",l1) |
|
|
1335 | 1335 | ##print("l2",l2) |
|
|
1336 | 1336 | if len(l1)>0: |
|
|
1337 | 1337 | #angulos2 = self.fixData90(list_=l1,ang_=angulos) |
|
|
1338 | 1338 | #l1,l2 = self.get2List(angulos2) |
|
|
1339 | 1339 | ang1_,ang2_ = self.fixDataComp(ang_=angulos,list1_=l1,list2_=l2,tipo_case=tipo_case) |
|
|
1340 | 1340 | #ang1_ = self.fixData90HL(ang1_) |
|
|
1341 | 1341 | #ang2_ = self.fixData90HL(ang2_) |
|
|
1342 | 1342 | else: |
|
|
1343 | 1343 | ang1_= angulos |
|
|
1344 | 1344 | ang2_= angulos |
|
|
1345 | 1345 | return ang1_,ang2_ |
|
|
1346 | 1346 | |
|
|
1347 | 1347 | |
|
|
1348 | 1348 | def replaceNAN(self,data_weather,data_ele,val): |
|
|
1349 | 1349 | data= data_ele |
|
|
1350 | 1350 | data_T= data_weather |
|
|
1351 | 1351 | if data.shape[0]> data_T.shape[0]: |
|
|
1352 | 1352 | data_N = numpy.ones( [data.shape[0],data_T.shape[1]]) |
|
|
1353 | 1353 | c = 0 |
|
|
1354 | 1354 | for i in range(len(data)): |
|
|
1355 | 1355 | if numpy.isnan(data[i]): |
|
|
1356 | 1356 | data_N[i,:]=numpy.ones(data_T.shape[1])*numpy.nan |
|
|
1357 | 1357 | else: |
|
|
1358 | 1358 | data_N[i,:]=data_T[c,:] |
|
|
1359 | 1359 | c=c+1 |
|
|
1360 | 1360 | return data_N |
|
|
1361 | 1361 | else: |
|
|
1362 | 1362 | for i in range(len(data)): |
|
|
1363 | 1363 | if numpy.isnan(data[i]): |
|
|
1364 | 1364 | data_T[i,:]=numpy.ones(data_T.shape[1])*numpy.nan |
|
|
1365 | 1365 | return data_T |
|
|
1366 | 1366 | |
|
|
1367 | 1367 | def check_case(self,data_ele,ang_max,ang_min): |
|
|
1368 | 1368 | start = data_ele[0] |
|
|
1369 | 1369 | end = data_ele[-1] |
|
|
1370 | 1370 | number = (end-start) |
|
|
1371 | 1371 | len_ang=len(data_ele) |
|
|
1372 | 1372 | print("start",start) |
|
|
1373 | 1373 | print("end",end) |
|
|
1374 | 1374 | print("number",number) |
|
|
1375 | 1375 | |
|
|
1376 | 1376 | print("len_ang",len_ang) |
|
|
1377 | 1377 | |
|
|
1378 | 1378 | #exit(1) |
|
|
1379 | 1379 | |
|
|
1380 | 1380 | if start<end and (round(abs(number)+1)>=len_ang or (numpy.argmin(data_ele)==0)):#caso subida |
|
|
1381 | 1381 | return 0 |
|
|
1382 | 1382 | #elif start>end and (round(abs(number)+1)>=len_ang or(numpy.argmax(data_ele)==0)):#caso bajada |
|
|
1383 | 1383 | # return 1 |
|
|
1384 | 1384 | elif round(abs(number)+1)>=len_ang and (start>end or(numpy.argmax(data_ele)==0)):#caso bajada |
|
|
1385 | 1385 | return 1 |
|
|
1386 | 1386 | elif round(abs(number)+1)<len_ang and data_ele[-2]>data_ele[-1]:# caso BAJADA CAMBIO ANG MAX |
|
|
1387 | 1387 | return 2 |
|
|
1388 | 1388 | elif round(abs(number)+1)<len_ang and data_ele[-2]<data_ele[-1] :# caso SUBIDA CAMBIO ANG MIN |
|
|
1389 | 1389 | return 3 |
|
|
1390 | 1390 | |
|
|
1391 | 1391 | |
|
|
1392 | 1392 | def const_ploteo(self,val_ch,data_weather,data_ele,step,res,ang_max,ang_min,case_flag): |
|
|
1393 | 1393 | ang_max= ang_max |
|
|
1394 | 1394 | ang_min= ang_min |
|
|
1395 | 1395 | data_weather=data_weather |
|
|
1396 | 1396 | val_ch=val_ch |
|
|
1397 | 1397 | ##print("*********************DATA WEATHER**************************************") |
|
|
1398 | 1398 | ##print(data_weather) |
|
|
1399 | 1399 | if self.ini==0: |
|
|
1400 | 1400 | ''' |
|
|
1401 | 1401 | print("**********************************************") |
|
|
1402 | 1402 | print("**********************************************") |
|
|
1403 | 1403 | print("***************ini**************") |
|
|
1404 | 1404 | print("**********************************************") |
|
|
1405 | 1405 | print("**********************************************") |
|
|
1406 | 1406 | ''' |
|
|
1407 | 1407 | #print("data_ele",data_ele) |
|
|
1408 | 1408 | #---------------------------------------------------------- |
|
|
1409 | 1409 | tipo_case = case_flag[-1] |
|
|
1410 | 1410 | #tipo_case = self.check_case(data_ele,ang_max,ang_min) |
|
|
1411 | 1411 | print("check_case",tipo_case) |
|
|
1412 | 1412 | #exit(1) |
|
|
1413 | 1413 | #--------------------- new ------------------------- |
|
|
1414 | 1414 | data_ele_new ,data_ele_old= self.globalCheckPED(data_ele,tipo_case) |
|
|
1415 | 1415 | |
|
|
1416 | 1416 | #-------------------------CAMBIOS RHI--------------------------------- |
|
|
1417 | 1417 | start= ang_min |
|
|
1418 | 1418 | end = ang_max |
|
|
1419 | 1419 | n= (ang_max-ang_min)/res |
|
|
1420 | 1420 | #------ new |
|
|
1421 | 1421 | self.start_data_ele = data_ele_new[0] |
|
|
1422 | 1422 | self.end_data_ele = data_ele_new[-1] |
|
|
1423 | 1423 | if tipo_case==0 or tipo_case==3: # SUBIDA |
|
|
1424 | 1424 | n1= round(self.start_data_ele)- start |
|
|
1425 | 1425 | n2= end - round(self.end_data_ele) |
|
|
1426 | 1426 | print(self.start_data_ele) |
|
|
1427 | 1427 | print(self.end_data_ele) |
|
|
1428 | 1428 | if n1>0: |
|
|
1429 | 1429 | ele1= numpy.linspace(ang_min+1,self.start_data_ele-1,n1) |
|
|
1430 | 1430 | ele1_nan= numpy.ones(n1)*numpy.nan |
|
|
1431 | 1431 | data_ele = numpy.hstack((ele1,data_ele_new)) |
|
|
1432 | 1432 | print("ele1_nan",ele1_nan.shape) |
|
|
1433 | 1433 | print("data_ele_old",data_ele_old.shape) |
|
|
1434 | 1434 | data_ele_old = numpy.hstack((ele1_nan,data_ele_old)) |
|
|
1435 | 1435 | if n2>0: |
|
|
1436 | 1436 | ele2= numpy.linspace(self.end_data_ele+1,end,n2) |
|
|
1437 | 1437 | ele2_nan= numpy.ones(n2)*numpy.nan |
|
|
1438 | 1438 | data_ele = numpy.hstack((data_ele,ele2)) |
|
|
1439 | 1439 | print("ele2_nan",ele2_nan.shape) |
|
|
1440 | 1440 | print("data_ele_old",data_ele_old.shape) |
|
|
1441 | 1441 | data_ele_old = numpy.hstack((data_ele_old,ele2_nan)) |
|
|
1442 | 1442 | |
|
|
1443 | 1443 | if tipo_case==1 or tipo_case==2: # BAJADA |
|
|
1444 | 1444 | data_ele_new = data_ele_new[::-1] # reversa |
|
|
1445 | 1445 | data_ele_old = data_ele_old[::-1]# reversa |
|
|
1446 | 1446 | data_weather = data_weather[::-1,:]# reversa |
|
|
1447 | 1447 | vec= numpy.where(data_ele_new<ang_max) |
|
|
1448 | 1448 | data_ele_new = data_ele_new[vec] |
|
|
1449 | 1449 | data_ele_old = data_ele_old[vec] |
|
|
1450 | 1450 | data_weather = data_weather[vec[0]] |
|
|
1451 | 1451 | vec2= numpy.where(0<data_ele_new) |
|
|
1452 | 1452 | data_ele_new = data_ele_new[vec2] |
|
|
1453 | 1453 | data_ele_old = data_ele_old[vec2] |
|
|
1454 | 1454 | data_weather = data_weather[vec2[0]] |
|
|
1455 | 1455 | self.start_data_ele = data_ele_new[0] |
|
|
1456 | 1456 | self.end_data_ele = data_ele_new[-1] |
|
|
1457 | 1457 | |
|
|
1458 | 1458 | n1= round(self.start_data_ele)- start |
|
|
1459 | 1459 | n2= end - round(self.end_data_ele)-1 |
|
|
1460 | 1460 | print(self.start_data_ele) |
|
|
1461 | 1461 | print(self.end_data_ele) |
|
|
1462 | 1462 | if n1>0: |
|
|
1463 | 1463 | ele1= numpy.linspace(ang_min+1,self.start_data_ele-1,n1) |
|
|
1464 | 1464 | ele1_nan= numpy.ones(n1)*numpy.nan |
|
|
1465 | 1465 | data_ele = numpy.hstack((ele1,data_ele_new)) |
|
|
1466 | 1466 | data_ele_old = numpy.hstack((ele1_nan,data_ele_old)) |
|
|
1467 | 1467 | if n2>0: |
|
|
1468 | 1468 | ele2= numpy.linspace(self.end_data_ele+1,end,n2) |
|
|
1469 | 1469 | ele2_nan= numpy.ones(n2)*numpy.nan |
|
|
1470 | 1470 | data_ele = numpy.hstack((data_ele,ele2)) |
|
|
1471 | 1471 | data_ele_old = numpy.hstack((data_ele_old,ele2_nan)) |
|
|
1472 | 1472 | # RADAR |
|
|
1473 | 1473 | # NOTA data_ele y data_weather es la variable que retorna |
|
|
1474 | 1474 | val_mean = numpy.mean(data_weather[:,-1]) |
|
|
1475 | 1475 | self.val_mean = val_mean |
|
|
1476 | 1476 | data_weather = self.replaceNAN(data_weather=data_weather,data_ele=data_ele_old,val=self.val_mean) |
|
|
1477 | 1477 | print("eleold",data_ele_old) |
|
|
1478 | 1478 | print(self.data_ele_tmp[val_ch]) |
|
|
1479 | 1479 | print(data_ele_old.shape[0]) |
|
|
1480 | 1480 | print(self.data_ele_tmp[val_ch].shape[0]) |
|
|
1481 | 1481 | if (data_ele_old.shape[0]==91 or self.data_ele_tmp[val_ch].shape[0]==91): |
|
|
1482 | 1482 | import sys |
|
|
1483 | 1483 | print("EXIT",self.ini) |
|
|
1484 | 1484 | |
|
|
1485 | 1485 | sys.exit(1) |
|
|
1486 | 1486 | self.data_ele_tmp[val_ch]= data_ele_old |
|
|
1487 | 1487 | else: |
|
|
1488 | 1488 | #print("**********************************************") |
|
|
1489 | 1489 | #print("****************VARIABLE**********************") |
|
|
1490 | 1490 | #-------------------------CAMBIOS RHI--------------------------------- |
|
|
1491 | 1491 | #--------------------------------------------------------------------- |
|
|
1492 | 1492 | ##print("INPUT data_ele",data_ele) |
|
|
1493 | 1493 | flag=0 |
|
|
1494 | 1494 | start_ele = self.res_ele[0] |
|
|
1495 | 1495 | #tipo_case = self.check_case(data_ele,ang_max,ang_min) |
|
|
1496 | 1496 | tipo_case = case_flag[-1] |
|
|
1497 | 1497 | #print("TIPO DE DATA",tipo_case) |
|
|
1498 | 1498 | #-----------new------------ |
|
|
1499 | 1499 | data_ele ,data_ele_old = self.globalCheckPED(data_ele,tipo_case) |
|
|
1500 | 1500 | data_weather = self.replaceNAN(data_weather=data_weather,data_ele=data_ele_old,val=self.val_mean) |
|
|
1501 | 1501 | |
|
|
1502 | 1502 | #-------------------------------NEW RHI ITERATIVO------------------------- |
|
|
1503 | 1503 | |
|
|
1504 | 1504 | if tipo_case==0 : # SUBIDA |
|
|
1505 | 1505 | vec = numpy.where(data_ele<ang_max) |
|
|
1506 | 1506 | data_ele = data_ele[vec] |
|
|
1507 | 1507 | data_ele_old = data_ele_old[vec] |
|
|
1508 | 1508 | data_weather = data_weather[vec[0]] |
|
|
1509 | 1509 | |
|
|
1510 | 1510 | vec2 = numpy.where(0<data_ele) |
|
|
1511 | 1511 | data_ele= data_ele[vec2] |
|
|
1512 | 1512 | data_ele_old= data_ele_old[vec2] |
|
|
1513 | 1513 | ##print(data_ele_new) |
|
|
1514 | 1514 | data_weather= data_weather[vec2[0]] |
|
|
1515 | 1515 | |
|
|
1516 | 1516 | new_i_ele = int(round(data_ele[0])) |
|
|
1517 | 1517 | new_f_ele = int(round(data_ele[-1])) |
|
|
1518 | 1518 | #print(new_i_ele) |
|
|
1519 | 1519 | #print(new_f_ele) |
|
|
1520 | 1520 | #print(data_ele,len(data_ele)) |
|
|
1521 | 1521 | #print(data_ele_old,len(data_ele_old)) |
|
|
1522 | 1522 | if new_i_ele< 2: |
|
|
1523 | 1523 | self.data_ele_tmp[val_ch] = numpy.ones(ang_max-ang_min)*numpy.nan |
|
|
1524 | 1524 | self.res_weather[val_ch] = self.replaceNAN(data_weather=self.res_weather[val_ch],data_ele=self.data_ele_tmp[val_ch],val=self.val_mean) |
|
|
1525 | 1525 | self.data_ele_tmp[val_ch][new_i_ele:new_i_ele+len(data_ele)]=data_ele_old |
|
|
1526 | 1526 | self.res_ele[new_i_ele:new_i_ele+len(data_ele)]= data_ele |
|
|
1527 | 1527 | self.res_weather[val_ch][new_i_ele:new_i_ele+len(data_ele),:]= data_weather |
|
|
1528 | 1528 | data_ele = self.res_ele |
|
|
1529 | 1529 | data_weather = self.res_weather[val_ch] |
|
|
1530 | 1530 | |
|
|
1531 | 1531 | elif tipo_case==1 : #BAJADA |
|
|
1532 | 1532 | data_ele = data_ele[::-1] # reversa |
|
|
1533 | 1533 | data_ele_old = data_ele_old[::-1]# reversa |
|
|
1534 | 1534 | data_weather = data_weather[::-1,:]# reversa |
|
|
1535 | 1535 | vec= numpy.where(data_ele<ang_max) |
|
|
1536 | 1536 | data_ele = data_ele[vec] |
|
|
1537 | 1537 | data_ele_old = data_ele_old[vec] |
|
|
1538 | 1538 | data_weather = data_weather[vec[0]] |
|
|
1539 | 1539 | vec2= numpy.where(0<data_ele) |
|
|
1540 | 1540 | data_ele = data_ele[vec2] |
|
|
1541 | 1541 | data_ele_old = data_ele_old[vec2] |
|
|
1542 | 1542 | data_weather = data_weather[vec2[0]] |
|
|
1543 | 1543 | |
|
|
1544 | 1544 | |
|
|
1545 | 1545 | new_i_ele = int(round(data_ele[0])) |
|
|
1546 | 1546 | new_f_ele = int(round(data_ele[-1])) |
|
|
1547 | 1547 | #print(data_ele) |
|
|
1548 | 1548 | #print(ang_max) |
|
|
1549 | 1549 | #print(data_ele_old) |
|
|
1550 | 1550 | if new_i_ele <= 1: |
|
|
1551 | 1551 | new_i_ele = 1 |
|
|
1552 | 1552 | if round(data_ele[-1])>=ang_max-1: |
|
|
1553 | 1553 | self.data_ele_tmp[val_ch] = numpy.ones(ang_max-ang_min)*numpy.nan |
|
|
1554 | 1554 | self.res_weather[val_ch] = self.replaceNAN(data_weather=self.res_weather[val_ch],data_ele=self.data_ele_tmp[val_ch],val=self.val_mean) |
|
|
1555 | 1555 | self.data_ele_tmp[val_ch][new_i_ele-1:new_i_ele+len(data_ele)-1]=data_ele_old |
|
|
1556 | 1556 | self.res_ele[new_i_ele-1:new_i_ele+len(data_ele)-1]= data_ele |
|
|
1557 | 1557 | self.res_weather[val_ch][new_i_ele-1:new_i_ele+len(data_ele)-1,:]= data_weather |
|
|
1558 | 1558 | data_ele = self.res_ele |
|
|
1559 | 1559 | data_weather = self.res_weather[val_ch] |
|
|
1560 | 1560 | |
|
|
1561 | 1561 | elif tipo_case==2: #bajada |
|
|
1562 | 1562 | vec = numpy.where(data_ele<ang_max) |
|
|
1563 | 1563 | data_ele = data_ele[vec] |
|
|
1564 | 1564 | data_weather= data_weather[vec[0]] |
|
|
1565 | 1565 | |
|
|
1566 | 1566 | len_vec = len(vec) |
|
|
1567 | 1567 | data_ele_new = data_ele[::-1] # reversa |
|
|
1568 | 1568 | data_weather = data_weather[::-1,:] |
|
|
1569 | 1569 | new_i_ele = int(data_ele_new[0]) |
|
|
1570 | 1570 | new_f_ele = int(data_ele_new[-1]) |
|
|
1571 | 1571 | |
|
|
1572 | 1572 | n1= new_i_ele- ang_min |
|
|
1573 | 1573 | n2= ang_max - new_f_ele-1 |
|
|
1574 | 1574 | if n1>0: |
|
|
1575 | 1575 | ele1= numpy.linspace(ang_min+1,new_i_ele-1,n1) |
|
|
1576 | 1576 | ele1_nan= numpy.ones(n1)*numpy.nan |
|
|
1577 | 1577 | data_ele = numpy.hstack((ele1,data_ele_new)) |
|
|
1578 | 1578 | data_ele_old = numpy.hstack((ele1_nan,data_ele_new)) |
|
|
1579 | 1579 | if n2>0: |
|
|
1580 | 1580 | ele2= numpy.linspace(new_f_ele+1,ang_max,n2) |
|
|
1581 | 1581 | ele2_nan= numpy.ones(n2)*numpy.nan |
|
|
1582 | 1582 | data_ele = numpy.hstack((data_ele,ele2)) |
|
|
1583 | 1583 | data_ele_old = numpy.hstack((data_ele_old,ele2_nan)) |
|
|
1584 | 1584 | |
|
|
1585 | 1585 | self.data_ele_tmp[val_ch] = data_ele_old |
|
|
1586 | 1586 | self.res_ele = data_ele |
|
|
1587 | 1587 | self.res_weather[val_ch] = self.replaceNAN(data_weather=data_weather,data_ele=data_ele_old,val=self.val_mean) |
|
|
1588 | 1588 | data_ele = self.res_ele |
|
|
1589 | 1589 | data_weather = self.res_weather[val_ch] |
|
|
1590 | 1590 | |
|
|
1591 | 1591 | elif tipo_case==3:#subida |
|
|
1592 | 1592 | vec = numpy.where(0<data_ele) |
|
|
1593 | 1593 | data_ele= data_ele[vec] |
|
|
1594 | 1594 | data_ele_new = data_ele |
|
|
1595 | 1595 | data_ele_old= data_ele_old[vec] |
|
|
1596 | 1596 | data_weather= data_weather[vec[0]] |
|
|
1597 | 1597 | pos_ini = numpy.argmin(data_ele) |
|
|
1598 | 1598 | if pos_ini>0: |
|
|
1599 | 1599 | len_vec= len(data_ele) |
|
|
1600 | 1600 | vec3 = numpy.linspace(pos_ini,len_vec-1,len_vec-pos_ini).astype(int) |
|
|
1601 | 1601 | #print(vec3) |
|
|
1602 | 1602 | data_ele= data_ele[vec3] |
|
|
1603 | 1603 | data_ele_new = data_ele |
|
|
1604 | 1604 | data_ele_old= data_ele_old[vec3] |
|
|
1605 | 1605 | data_weather= data_weather[vec3] |
|
|
1606 | 1606 | |
|
|
1607 | 1607 | new_i_ele = int(data_ele_new[0]) |
|
|
1608 | 1608 | new_f_ele = int(data_ele_new[-1]) |
|
|
1609 | 1609 | n1= new_i_ele- ang_min |
|
|
1610 | 1610 | n2= ang_max - new_f_ele-1 |
|
|
1611 | 1611 | if n1>0: |
|
|
1612 | 1612 | ele1= numpy.linspace(ang_min+1,new_i_ele-1,n1) |
|
|
1613 | 1613 | ele1_nan= numpy.ones(n1)*numpy.nan |
|
|
1614 | 1614 | data_ele = numpy.hstack((ele1,data_ele_new)) |
|
|
1615 | 1615 | data_ele_old = numpy.hstack((ele1_nan,data_ele_new)) |
|
|
1616 | 1616 | if n2>0: |
|
|
1617 | 1617 | ele2= numpy.linspace(new_f_ele+1,ang_max,n2) |
|
|
1618 | 1618 | ele2_nan= numpy.ones(n2)*numpy.nan |
|
|
1619 | 1619 | data_ele = numpy.hstack((data_ele,ele2)) |
|
|
1620 | 1620 | data_ele_old = numpy.hstack((data_ele_old,ele2_nan)) |
|
|
1621 | 1621 | |
|
|
1622 | 1622 | self.data_ele_tmp[val_ch] = data_ele_old |
|
|
1623 | 1623 | self.res_ele = data_ele |
|
|
1624 | 1624 | self.res_weather[val_ch] = self.replaceNAN(data_weather=data_weather,data_ele=data_ele_old,val=self.val_mean) |
|
|
1625 | 1625 | data_ele = self.res_ele |
|
|
1626 | 1626 | data_weather = self.res_weather[val_ch] |
|
|
1627 | 1627 | #print("self.data_ele_tmp",self.data_ele_tmp) |
|
|
1628 | 1628 | return data_weather,data_ele |
|
|
1629 | 1629 | |
|
|
1630 | 1630 | |
|
|
1631 | 1631 | def plot(self): |
|
|
1632 | 1632 | thisDatetime = datetime.datetime.utcfromtimestamp(self.data.times[-1]).strftime('%Y-%m-%d %H:%M:%S') |
|
|
1633 | 1633 | data = self.data[-1] |
|
|
1634 | 1634 | r = self.data.yrange |
|
|
1635 | 1635 | delta_height = r[1]-r[0] |
|
|
1636 | 1636 | r_mask = numpy.where(r>=0)[0] |
|
|
1637 | 1637 | ##print("delta_height",delta_height) |
|
|
1638 | 1638 | #print("r_mask",r_mask,len(r_mask)) |
|
|
1639 | 1639 | r = numpy.arange(len(r_mask))*delta_height |
|
|
1640 | 1640 | self.y = 2*r |
|
|
1641 | 1641 | res = 1 |
|
|
1642 | 1642 | ###print("data['weather'].shape[0]",data['weather'].shape[0]) |
|
|
1643 | 1643 | ang_max = self.ang_max |
|
|
1644 | 1644 | ang_min = self.ang_min |
|
|
1645 | 1645 | var_ang =ang_max - ang_min |
|
|
1646 | 1646 | step = (int(var_ang)/(res*data['weather'].shape[0])) |
|
|
1647 | 1647 | ###print("step",step) |
|
|
1648 | 1648 | #-------------------------------------------------------- |
|
|
1649 | 1649 | ##print('weather',data['weather'].shape) |
|
|
1650 | 1650 | ##print('ele',data['ele'].shape) |
|
|
1651 | 1651 | |
|
|
1652 | 1652 | ###self.res_weather, self.res_ele = self.const_ploteo(data_weather=data['weather'][:,r_mask],data_ele=data['ele'],step=step,res=res,ang_max=ang_max,ang_min=ang_min) |
|
|
1653 | 1653 | ###self.res_azi = numpy.mean(data['azi']) |
|
|
1654 | 1654 | ###print("self.res_ele",self.res_ele) |
|
|
1655 | 1655 | plt.clf() |
|
|
1656 | 1656 | subplots = [121, 122] |
|
|
1657 | 1657 | try: |
|
|
1658 | 1658 | if self.data[-2]['ele'].max()<data['ele'].max(): |
|
|
1659 | 1659 | self.ini=0 |
|
|
1660 | 1660 | except: |
|
|
1661 | 1661 | pass |
|
|
1662 | 1662 | if self.ini==0: |
|
|
1663 | 1663 | self.data_ele_tmp = numpy.ones([self.nplots,int(var_ang)])*numpy.nan |
|
|
1664 | 1664 | self.res_weather= numpy.ones([self.nplots,int(var_ang),len(r_mask)])*numpy.nan |
|
|
1665 | 1665 | print("SHAPE",self.data_ele_tmp.shape) |
|
|
1666 | 1666 | |
|
|
1667 | 1667 | for i,ax in enumerate(self.axes): |
|
|
1668 | 1668 | self.res_weather[i], self.res_ele = self.const_ploteo(val_ch=i, data_weather=data['weather'][i][:,r_mask],data_ele=data['ele'],step=step,res=res,ang_max=ang_max,ang_min=ang_min,case_flag=self.data['case_flag']) |
|
|
1669 | 1669 | self.res_azi = numpy.mean(data['azi']) |
|
|
1670 | 1670 | |
|
|
1671 | 1671 | if ax.firsttime: |
|
|
1672 | 1672 | #plt.clf() |
|
|
1673 | 1673 | print("Frist Plot") |
|
|
1674 | 1674 | cgax, pm = wrl.vis.plot_rhi(self.res_weather[i],r=r,th=self.res_ele,ax=subplots[i], proj='cg',vmin=20, vmax=80) |
|
|
1675 | 1675 | #fig=self.figures[0] |
|
|
1676 | 1676 | else: |
|
|
1677 | 1677 | #plt.clf() |
|
|
1678 | 1678 | print("ELSE PLOT") |
|
|
1679 | 1679 | cgax, pm = wrl.vis.plot_rhi(self.res_weather[i],r=r,th=self.res_ele,ax=subplots[i], proj='cg',vmin=20, vmax=80) |
|
|
1680 | 1680 | caax = cgax.parasites[0] |
|
|
1681 | 1681 | paax = cgax.parasites[1] |
|
|
1682 | 1682 | cbar = plt.gcf().colorbar(pm, pad=0.075) |
|
|
1683 | 1683 | caax.set_xlabel('x_range [km]') |
|
|
1684 | 1684 | caax.set_ylabel('y_range [km]') |
|
|
1685 | 1685 | plt.text(1.0, 1.05, 'Elevacion '+str(thisDatetime)+" Step "+str(self.ini)+ " Azi: "+str(round(self.res_azi,2)), transform=caax.transAxes, va='bottom',ha='right') |
|
|
1686 | 1686 | print("***************************self.ini****************************",self.ini) |
|
|
1687 | 1687 | self.ini= self.ini+1 |
|
|
1688 | 1688 | |
|
|
1689 | 1689 | |
|
|
1690 | 1690 | |
|
|
1691 | 1691 | |
|
|
1692 | 1692 | |
|
|
1693 | 1693 | class WeatherRHI_vRF4_Plot(Plot): |
|
|
1694 | 1694 | CODE = 'RHI' |
|
|
1695 | 1695 | plot_name = 'RHI' |
|
|
1696 | 1696 | #plot_type = 'rhistyle' |
|
|
1697 | 1697 | buffering = False |
|
|
1698 | 1698 | |
|
|
1699 | 1699 | def setup(self): |
|
|
1700 | 1700 | |
|
|
1701 | 1701 | self.ncols = 1 |
|
|
1702 | 1702 | self.nrows = 1 |
|
|
1703 | 1703 | self.nplots= 1 |
|
|
1704 | 1704 | self.ylabel= 'Range [Km]' |
|
|
1705 | 1705 | self.xlabel= 'Range [Km]' |
|
|
1706 | 1706 | self.titles= ['RHI'] |
|
|
1707 | 1707 | self.polar = True |
|
|
1708 | 1708 | self.grid = True |
|
|
1709 | 1709 | if self.channels is not None: |
|
|
1710 | 1710 | self.nplots = len(self.channels) |
|
|
1711 | 1711 | self.nrows = len(self.channels) |
|
|
1712 | 1712 | else: |
|
|
1713 | 1713 | self.nplots = self.data.shape(self.CODE)[0] |
|
|
1714 | 1714 | self.nrows = self.nplots |
|
|
1715 | 1715 | self.channels = list(range(self.nplots)) |
|
|
1716 | 1716 | |
|
|
1717 | 1717 | if self.CODE == 'Power': |
|
|
1718 | 1718 | self.cb_label = r'Power (dB)' |
|
|
1719 | 1719 | elif self.CODE == 'Doppler': |
|
|
1720 | 1720 | self.cb_label = r'Velocity (m/s)' |
|
|
1721 | 1721 | self.colorbar=True |
|
|
1722 | 1722 | self.width =8 |
|
|
1723 | 1723 | self.height =8 |
|
|
1724 | 1724 | self.ini =0 |
|
|
1725 | 1725 | self.len_azi =0 |
|
|
1726 | 1726 | self.buffer_ini = None |
|
|
1727 | 1727 | self.buffer_ele = None |
|
|
1728 | 1728 | self.plots_adjust.update({'wspace': 0.4, 'hspace':0.4, 'left': 0.1, 'right': 0.9, 'bottom': 0.08}) |
|
|
1729 | 1729 | self.flag =0 |
|
|
1730 | 1730 | self.indicador= 0 |
|
|
1731 | 1731 | self.last_data_ele = None |
|
|
1732 | 1732 | self.val_mean = None |
|
|
1733 | 1733 | |
|
|
1734 | 1734 | def update(self, dataOut): |
|
|
1735 | 1735 | |
|
|
1736 | 1736 | data = {} |
|
|
1737 | 1737 | meta = {} |
|
|
1738 | 1738 | if hasattr(dataOut, 'dataPP_POWER'): |
|
|
1739 | 1739 | factor = 1 |
|
|
1740 | 1740 | if hasattr(dataOut, 'nFFTPoints'): |
|
|
1741 | 1741 | factor = dataOut.normFactor |
|
|
1742 | 1742 | |
|
|
1743 | 1743 | if 'pow' in self.attr_data[0].lower(): |
|
|
1744 | 1744 | data['data'] = 10*numpy.log10(getattr(dataOut, self.attr_data[0])/(factor)) |
|
|
1745 | 1745 | else: |
|
|
1746 | 1746 | data['data'] = getattr(dataOut, self.attr_data[0])/(factor) |
|
|
1747 | 1747 | |
|
|
1748 | 1748 | data['azi'] = dataOut.data_azi |
|
|
1749 | 1749 | data['ele'] = dataOut.data_ele |
|
|
1750 | 1750 | |
|
|
1751 | 1751 | return data, meta |
|
|
1752 | 1752 | |
|
|
1753 | 1753 | def plot(self): |
|
|
1754 | 1754 | data = self.data[-1] |
|
|
1755 | 1755 | r = self.data.yrange |
|
|
1756 | 1756 | delta_height = r[1]-r[0] |
|
|
1757 | 1757 | r_mask = numpy.where(r>=0)[0] |
|
|
1758 | 1758 | self.r_mask =r_mask |
|
|
1759 | 1759 | r = numpy.arange(len(r_mask))*delta_height |
|
|
1760 | 1760 | self.y = 2*r |
|
|
1761 | 1761 | |
|
|
1762 | 1762 | z = data['data'][self.channels[0]][:,r_mask] |
|
|
1763 | 1763 | |
|
|
1764 | 1764 | self.titles = [] |
|
|
1765 | 1765 | |
|
|
1766 | 1766 | self.ymax = self.ymax if self.ymax else numpy.nanmax(r) |
|
|
1767 | 1767 | self.ymin = self.ymin if self.ymin else numpy.nanmin(r) |
|
|
1768 | 1768 | self.zmax = self.zmax if self.zmax else numpy.nanmax(z) |
|
|
1769 | 1769 | self.zmin = self.zmin if self.zmin else numpy.nanmin(z) |
|
|
1770 | 1770 | self.ang_min = self.ang_min if self.ang_min else 0 |
|
|
1771 | 1771 | self.ang_max = self.ang_max if self.ang_max else 90 |
|
|
1772 | 1772 | |
|
|
1773 | 1773 | r, theta = numpy.meshgrid(r, numpy.radians(data['ele']) ) |
|
|
1774 | 1774 | |
|
|
1775 | 1775 | for i,ax in enumerate(self.axes): |
|
|
1776 | 1776 | |
|
|
1777 | 1777 | if ax.firsttime: |
|
|
1778 | 1778 | ax.set_xlim(numpy.radians(self.ang_min),numpy.radians(self.ang_max)) |
|
|
1779 | 1779 | ax.plt = ax.pcolormesh(theta, r, z, cmap=self.colormap, vmin=self.zmin, vmax=self.zmax) |
|
|
1780 | 1780 | |
|
|
1781 | 1781 | else: |
|
|
1782 | 1782 | ax.set_xlim(numpy.radians(self.ang_min),numpy.radians(self.ang_max)) |
|
|
1783 | 1783 | ax.plt = ax.pcolormesh(theta, r, z, cmap=self.colormap, vmin=self.zmin, vmax=self.zmax) |
|
|
1784 | 1784 | ax.grid(True) |
|
|
1785 | 1785 | if len(self.channels) !=1: |
|
|
1786 | 1786 | self.titles = ['RHI {} at AZ: {} Channel {}'.format(self.labels[x], str(round(numpy.mean(data['azi']),1)), x) for x in range(self.nrows)] |
|
|
1787 | 1787 | else: |
|
|
1788 | 1788 | self.titles = ['RHI {} at AZ: {} Channel {}'.format(self.labels[0], str(round(numpy.mean(data['azi']),1)), self.channels[0])] |
| @@ -1,208 +1,226 | |||
|
|
1 | 1 | ''' |
|
|
2 | 2 | Base clases to create Processing units and operations, the MPDecorator |
|
|
3 | 3 | must be used in plotting and writing operations to allow to run as an |
|
|
4 | 4 | external process. |
|
|
5 | 5 | ''' |
|
|
6 | 6 | |
|
|
7 | 7 | import os |
|
|
8 | 8 | import inspect |
|
|
9 | 9 | import zmq |
|
|
10 | 10 | import time |
|
|
11 | 11 | import pickle |
|
|
12 | 12 | import traceback |
|
|
13 | 13 | from threading import Thread |
|
|
14 | 14 | from multiprocessing import Process, Queue |
|
|
15 | 15 | from schainpy.utils import log |
|
|
16 | 16 | |
|
|
17 | 17 | QUEUE_SIZE = int(os.environ.get('QUEUE_MAX_SIZE', '10')) |
|
|
18 | 18 | |
|
|
19 | 19 | class ProcessingUnit(object): |
|
|
20 | 20 | ''' |
|
|
21 | 21 | Base class to create Signal Chain Units |
|
|
22 | 22 | ''' |
|
|
23 | 23 | |
|
|
24 | 24 | proc_type = 'processing' |
|
|
25 | 25 | |
|
|
26 | 26 | def __init__(self): |
|
|
27 | 27 | |
|
|
28 | 28 | self.dataIn = None |
|
|
29 | 29 | self.dataOut = None |
|
|
30 | 30 | self.isConfig = False |
|
|
31 | 31 | self.operations = [] |
|
|
32 | self.name = 'Test' | |
|
|
33 | self.inputs = [] | |
|
|
32 | 34 | |
|
|
33 | 35 | def setInput(self, unit): |
|
|
34 | 36 | |
|
|
35 | self.dataIn = unit.dataOut | |
|
|
37 | attr = 'dataIn' | |
|
|
38 | for i, u in enumerate(unit): | |
|
|
39 | if i==0: | |
|
|
40 | self.dataIn = u.dataOut | |
|
|
41 | self.inputs.append('dataIn') | |
|
|
42 | else: | |
|
|
43 | setattr(self, 'dataIn{}'.format(i), u.dataOut) | |
|
|
44 | self.inputs.append('dataIn{}'.format(i)) | |
|
|
36 | 45 | |
|
|
37 | 46 | def getAllowedArgs(self): |
|
|
38 | 47 | if hasattr(self, '__attrs__'): |
|
|
39 | 48 | return self.__attrs__ |
|
|
40 | 49 | else: |
|
|
41 | 50 | return inspect.getargspec(self.run).args |
|
|
42 | 51 | |
|
|
43 | 52 | def addOperation(self, conf, operation): |
|
|
44 | 53 | ''' |
|
|
45 | 54 | ''' |
|
|
46 | 55 | |
|
|
47 | 56 | self.operations.append((operation, conf.type, conf.getKwargs())) |
|
|
48 | 57 | |
|
|
49 | 58 | def getOperationObj(self, objId): |
|
|
50 | 59 | |
|
|
51 | 60 | if objId not in list(self.operations.keys()): |
|
|
52 | 61 | return None |
|
|
53 | 62 | |
|
|
54 | 63 | return self.operations[objId] |
|
|
55 | 64 | |
|
|
56 | 65 | def call(self, **kwargs): |
|
|
57 | 66 | ''' |
|
|
58 | 67 | ''' |
|
|
59 | 68 | |
|
|
60 | 69 | try: |
|
|
61 | 70 | if self.dataIn is not None and self.dataIn.flagNoData and not self.dataIn.error: |
|
|
62 | 71 | return self.dataIn.isReady() |
|
|
63 | 72 | elif self.dataIn is None or not self.dataIn.error: |
|
|
64 | 73 | self.run(**kwargs) |
|
|
65 | 74 | elif self.dataIn.error: |
|
|
66 | 75 | self.dataOut.error = self.dataIn.error |
|
|
67 | 76 | self.dataOut.flagNoData = True |
|
|
68 | 77 | except: |
|
|
69 | 78 | err = traceback.format_exc() |
|
|
70 | 79 | if 'SchainWarning' in err: |
|
|
71 | 80 | log.warning(err.split('SchainWarning:')[-1].split('\n')[0].strip(), self.name) |
|
|
72 | 81 | elif 'SchainError' in err: |
|
|
73 | 82 | log.error(err.split('SchainError:')[-1].split('\n')[0].strip(), self.name) |
|
|
74 | 83 | else: |
|
|
75 | 84 | log.error(err, self.name) |
|
|
76 | 85 | self.dataOut.error = True |
|
|
77 | 86 | ##### correcion de la declaracion Out |
|
|
78 | 87 | for op, optype, opkwargs in self.operations: |
|
|
79 | 88 | aux = self.dataOut.copy() |
|
|
80 | 89 | if optype == 'other' and not self.dataOut.flagNoData: |
|
|
81 | 90 | self.dataOut = op.run(self.dataOut, **opkwargs) |
|
|
82 | 91 | elif optype == 'external' and not self.dataOut.flagNoData: |
|
|
83 | 92 | #op.queue.put(self.dataOut) |
|
|
84 | 93 | op.queue.put(aux) |
|
|
85 | 94 | elif optype == 'external' and self.dataOut.error: |
|
|
86 | 95 | #op.queue.put(self.dataOut) |
|
|
87 | 96 | op.queue.put(aux) |
|
|
88 | 97 | |
|
|
89 | return 'Error' if self.dataOut.error else self.dataOut.isReady() | |
|
|
98 | try: | |
|
|
99 | if self.dataOut.runNextUnit: | |
|
|
100 | runNextUnit = self.dataOut.runNextUnit | |
|
|
101 | ||
|
|
102 | else: | |
|
|
103 | runNextUnit = self.dataOut.isReady() | |
|
|
104 | except: | |
|
|
105 | runNextUnit = self.dataOut.isReady() | |
|
|
106 | ||
|
|
107 | return 'Error' if self.dataOut.error else runNextUnit | |
|
|
90 | 108 | |
|
|
91 | 109 | def setup(self): |
|
|
92 | 110 | |
|
|
93 | 111 | raise NotImplementedError |
|
|
94 | 112 | |
|
|
95 | 113 | def run(self): |
|
|
96 | 114 | |
|
|
97 | 115 | raise NotImplementedError |
|
|
98 | 116 | |
|
|
99 | 117 | def close(self): |
|
|
100 | 118 | |
|
|
101 | 119 | return |
|
|
102 | 120 | |
|
|
103 | 121 | |
|
|
104 | 122 | class Operation(object): |
|
|
105 | 123 | |
|
|
106 | 124 | ''' |
|
|
107 | 125 | ''' |
|
|
108 | 126 | |
|
|
109 | 127 | proc_type = 'operation' |
|
|
110 | 128 | |
|
|
111 | 129 | def __init__(self): |
|
|
112 | 130 | |
|
|
113 | 131 | self.id = None |
|
|
114 | 132 | self.isConfig = False |
|
|
115 | 133 | |
|
|
116 | 134 | if not hasattr(self, 'name'): |
|
|
117 | 135 | self.name = self.__class__.__name__ |
|
|
118 | 136 | |
|
|
119 | 137 | def getAllowedArgs(self): |
|
|
120 | 138 | if hasattr(self, '__attrs__'): |
|
|
121 | 139 | return self.__attrs__ |
|
|
122 | 140 | else: |
|
|
123 | 141 | return inspect.getargspec(self.run).args |
|
|
124 | 142 | |
|
|
125 | 143 | def setup(self): |
|
|
126 | 144 | |
|
|
127 | 145 | self.isConfig = True |
|
|
128 | 146 | |
|
|
129 | 147 | raise NotImplementedError |
|
|
130 | 148 | |
|
|
131 | 149 | def run(self, dataIn, **kwargs): |
|
|
132 | 150 | """ |
|
|
133 | 151 | Realiza las operaciones necesarias sobre la dataIn.data y actualiza los |
|
|
134 | 152 | atributos del objeto dataIn. |
|
|
135 | 153 | |
|
|
136 | 154 | Input: |
|
|
137 | 155 | |
|
|
138 | 156 | dataIn : objeto del tipo JROData |
|
|
139 | 157 | |
|
|
140 | 158 | Return: |
|
|
141 | 159 | |
|
|
142 | 160 | None |
|
|
143 | 161 | |
|
|
144 | 162 | Affected: |
|
|
145 | 163 | __buffer : buffer de recepcion de datos. |
|
|
146 | 164 | |
|
|
147 | 165 | """ |
|
|
148 | 166 | if not self.isConfig: |
|
|
149 | 167 | self.setup(**kwargs) |
|
|
150 | 168 | |
|
|
151 | 169 | raise NotImplementedError |
|
|
152 | 170 | |
|
|
153 | 171 | def close(self): |
|
|
154 | 172 | |
|
|
155 | 173 | return |
|
|
156 | 174 | |
|
|
157 | 175 | |
|
|
158 | 176 | def MPDecorator(BaseClass): |
|
|
159 | 177 | """ |
|
|
160 | 178 | Multiprocessing class decorator |
|
|
161 | 179 | |
|
|
162 | 180 | This function add multiprocessing features to a BaseClass. |
|
|
163 | 181 | """ |
|
|
164 | 182 | |
|
|
165 | 183 | class MPClass(BaseClass, Process): |
|
|
166 | 184 | |
|
|
167 | 185 | def __init__(self, *args, **kwargs): |
|
|
168 | 186 | super(MPClass, self).__init__() |
|
|
169 | 187 | Process.__init__(self) |
|
|
170 | 188 | |
|
|
171 | 189 | self.args = args |
|
|
172 | 190 | self.kwargs = kwargs |
|
|
173 | 191 | self.t = time.time() |
|
|
174 | 192 | self.op_type = 'external' |
|
|
175 | 193 | self.name = BaseClass.__name__ |
|
|
176 | 194 | self.__doc__ = BaseClass.__doc__ |
|
|
177 | 195 | |
|
|
178 | 196 | if 'plot' in self.name.lower() and not self.name.endswith('_'): |
|
|
179 | 197 | self.name = '{}{}'.format(self.CODE.upper(), 'Plot') |
|
|
180 | 198 | |
|
|
181 | 199 | self.start_time = time.time() |
|
|
182 | 200 | self.err_queue = args[3] |
|
|
183 | 201 | self.queue = Queue(maxsize=QUEUE_SIZE) |
|
|
184 | 202 | self.myrun = BaseClass.run |
|
|
185 | 203 | |
|
|
186 | 204 | def run(self): |
|
|
187 | 205 | |
|
|
188 | 206 | while True: |
|
|
189 | 207 | |
|
|
190 | 208 | dataOut = self.queue.get() |
|
|
191 | 209 | |
|
|
192 | 210 | if not dataOut.error: |
|
|
193 | 211 | try: |
|
|
194 | 212 | BaseClass.run(self, dataOut, **self.kwargs) |
|
|
195 | 213 | except: |
|
|
196 | 214 | err = traceback.format_exc() |
|
|
197 | 215 | log.error(err, self.name) |
|
|
198 | 216 | else: |
|
|
199 | 217 | break |
|
|
200 | 218 | |
|
|
201 | 219 | self.close() |
|
|
202 | 220 | |
|
|
203 | 221 | def close(self): |
|
|
204 | 222 | |
|
|
205 | 223 | BaseClass.close(self) |
|
|
206 | 224 | log.success('Done...(Time:{:4.2f} secs)'.format(time.time()-self.start_time), self.name) |
|
|
207 | 225 | |
|
|
208 | 226 | return MPClass |
|
|
1 | NO CONTENT: modified file | |
| The requested commit or file is too big and content was truncated. Show full diff | |||
| @@ -1,1862 +1,1860 | |||
|
|
1 | 1 | import sys |
|
|
2 | 2 | import numpy,math |
|
|
3 | 3 | from scipy import interpolate |
|
|
4 | 4 | from schainpy.model.proc.jroproc_base import ProcessingUnit, Operation, MPDecorator |
|
|
5 | 5 | from schainpy.model.data.jrodata import Voltage,hildebrand_sekhon |
|
|
6 | 6 | from schainpy.utils import log |
|
|
7 | 7 | from time import time |
|
|
8 | 8 | |
|
|
9 | 9 | |
|
|
10 | 10 | |
|
|
11 | 11 | class VoltageProc(ProcessingUnit): |
|
|
12 | 12 | |
|
|
13 | 13 | def __init__(self): |
|
|
14 | 14 | |
|
|
15 | 15 | ProcessingUnit.__init__(self) |
|
|
16 | 16 | |
|
|
17 | 17 | self.dataOut = Voltage() |
|
|
18 | 18 | self.flip = 1 |
|
|
19 | 19 | self.setupReq = False |
|
|
20 | 20 | |
|
|
21 | 21 | def run(self): |
|
|
22 | 22 | |
|
|
23 | 23 | if self.dataIn.type == 'AMISR': |
|
|
24 | 24 | self.__updateObjFromAmisrInput() |
|
|
25 | 25 | |
|
|
26 | 26 | if self.dataIn.type == 'Voltage': |
|
|
27 | 27 | self.dataOut.copy(self.dataIn) |
|
|
28 | 28 | |
|
|
29 | 29 | def __updateObjFromAmisrInput(self): |
|
|
30 | 30 | |
|
|
31 | 31 | self.dataOut.timeZone = self.dataIn.timeZone |
|
|
32 | 32 | self.dataOut.dstFlag = self.dataIn.dstFlag |
|
|
33 | 33 | self.dataOut.errorCount = self.dataIn.errorCount |
|
|
34 | 34 | self.dataOut.useLocalTime = self.dataIn.useLocalTime |
|
|
35 | 35 | |
|
|
36 | 36 | self.dataOut.flagNoData = self.dataIn.flagNoData |
|
|
37 | 37 | self.dataOut.data = self.dataIn.data |
|
|
38 | 38 | self.dataOut.utctime = self.dataIn.utctime |
|
|
39 | 39 | self.dataOut.channelList = self.dataIn.channelList |
|
|
40 | 40 | #self.dataOut.timeInterval = self.dataIn.timeInterval |
|
|
41 | 41 | self.dataOut.heightList = self.dataIn.heightList |
|
|
42 | 42 | self.dataOut.nProfiles = self.dataIn.nProfiles |
|
|
43 | 43 | |
|
|
44 | 44 | self.dataOut.nCohInt = self.dataIn.nCohInt |
|
|
45 | 45 | self.dataOut.ippSeconds = self.dataIn.ippSeconds |
|
|
46 | 46 | self.dataOut.frequency = self.dataIn.frequency |
|
|
47 | 47 | |
|
|
48 | 48 | self.dataOut.azimuth = self.dataIn.azimuth |
|
|
49 | 49 | self.dataOut.zenith = self.dataIn.zenith |
|
|
50 | 50 | |
|
|
51 | 51 | self.dataOut.beam.codeList = self.dataIn.beam.codeList |
|
|
52 | 52 | self.dataOut.beam.azimuthList = self.dataIn.beam.azimuthList |
|
|
53 | 53 | self.dataOut.beam.zenithList = self.dataIn.beam.zenithList |
|
|
54 | 54 | |
|
|
55 | 55 | |
|
|
56 | 56 | class selectChannels(Operation): |
|
|
57 | 57 | |
|
|
58 | 58 | def run(self, dataOut, channelList): |
|
|
59 | 59 | |
|
|
60 | 60 | channelIndexList = [] |
|
|
61 | 61 | self.dataOut = dataOut |
|
|
62 | 62 | for channel in channelList: |
|
|
63 | 63 | if channel not in self.dataOut.channelList: |
|
|
64 | 64 | raise ValueError("Channel %d is not in %s" %(channel, str(self.dataOut.channelList))) |
|
|
65 | 65 | |
|
|
66 | 66 | index = self.dataOut.channelList.index(channel) |
|
|
67 | 67 | channelIndexList.append(index) |
|
|
68 | 68 | self.selectChannelsByIndex(channelIndexList) |
|
|
69 | 69 | return self.dataOut |
|
|
70 | 70 | |
|
|
71 | 71 | def selectChannelsByIndex(self, channelIndexList): |
|
|
72 | 72 | """ |
|
|
73 | 73 | Selecciona un bloque de datos en base a canales segun el channelIndexList |
|
|
74 | 74 | |
|
|
75 | 75 | Input: |
|
|
76 | 76 | channelIndexList : lista sencilla de canales a seleccionar por ej. [2,3,7] |
|
|
77 | 77 | |
|
|
78 | 78 | Affected: |
|
|
79 | 79 | self.dataOut.data |
|
|
80 | 80 | self.dataOut.channelIndexList |
|
|
81 | 81 | self.dataOut.nChannels |
|
|
82 | 82 | self.dataOut.m_ProcessingHeader.totalSpectra |
|
|
83 | 83 | self.dataOut.systemHeaderObj.numChannels |
|
|
84 | 84 | self.dataOut.m_ProcessingHeader.blockSize |
|
|
85 | 85 | |
|
|
86 | 86 | Return: |
|
|
87 | 87 | None |
|
|
88 | 88 | """ |
|
|
89 | 89 | |
|
|
90 | 90 | for channelIndex in channelIndexList: |
|
|
91 | 91 | if channelIndex not in self.dataOut.channelIndexList: |
|
|
92 | 92 | raise ValueError("The value %d in channelIndexList is not valid" %channelIndex) |
|
|
93 | 93 | |
|
|
94 | 94 | if self.dataOut.type == 'Voltage': |
|
|
95 | 95 | if self.dataOut.flagDataAsBlock: |
|
|
96 | 96 | """ |
|
|
97 | 97 | Si la data es obtenida por bloques, dimension = [nChannels, nProfiles, nHeis] |
|
|
98 | 98 | """ |
|
|
99 | 99 | data = self.dataOut.data[channelIndexList,:,:] |
|
|
100 | 100 | else: |
|
|
101 | 101 | data = self.dataOut.data[channelIndexList,:] |
|
|
102 | 102 | |
|
|
103 | 103 | self.dataOut.data = data |
|
|
104 | 104 | # self.dataOut.channelList = [self.dataOut.channelList[i] for i in channelIndexList] |
|
|
105 | 105 | self.dataOut.channelList = range(len(channelIndexList)) |
|
|
106 | 106 | |
|
|
107 | 107 | elif self.dataOut.type == 'Spectra': |
|
|
108 | 108 | data_spc = self.dataOut.data_spc[channelIndexList, :] |
|
|
109 | 109 | data_dc = self.dataOut.data_dc[channelIndexList, :] |
|
|
110 | 110 | |
|
|
111 | 111 | self.dataOut.data_spc = data_spc |
|
|
112 | 112 | self.dataOut.data_dc = data_dc |
|
|
113 | 113 | |
|
|
114 | 114 | # self.dataOut.channelList = [self.dataOut.channelList[i] for i in channelIndexList] |
|
|
115 | 115 | self.dataOut.channelList = range(len(channelIndexList)) |
|
|
116 | 116 | self.__selectPairsByChannel(channelIndexList) |
|
|
117 | 117 | |
|
|
118 | 118 | return 1 |
|
|
119 | 119 | |
|
|
120 | 120 | def __selectPairsByChannel(self, channelList=None): |
|
|
121 | 121 | |
|
|
122 | 122 | if channelList == None: |
|
|
123 | 123 | return |
|
|
124 | 124 | |
|
|
125 | 125 | pairsIndexListSelected = [] |
|
|
126 | 126 | for pairIndex in self.dataOut.pairsIndexList: |
|
|
127 | 127 | # First pair |
|
|
128 | 128 | if self.dataOut.pairsList[pairIndex][0] not in channelList: |
|
|
129 | 129 | continue |
|
|
130 | 130 | # Second pair |
|
|
131 | 131 | if self.dataOut.pairsList[pairIndex][1] not in channelList: |
|
|
132 | 132 | continue |
|
|
133 | 133 | |
|
|
134 | 134 | pairsIndexListSelected.append(pairIndex) |
|
|
135 | 135 | |
|
|
136 | 136 | if not pairsIndexListSelected: |
|
|
137 | 137 | self.dataOut.data_cspc = None |
|
|
138 | 138 | self.dataOut.pairsList = [] |
|
|
139 | 139 | return |
|
|
140 | 140 | |
|
|
141 | 141 | self.dataOut.data_cspc = self.dataOut.data_cspc[pairsIndexListSelected] |
|
|
142 | 142 | self.dataOut.pairsList = [self.dataOut.pairsList[i] |
|
|
143 | 143 | for i in pairsIndexListSelected] |
|
|
144 | 144 | |
|
|
145 | 145 | return |
|
|
146 | 146 | |
|
|
147 | 147 | class selectHeights(Operation): |
|
|
148 | 148 | |
|
|
149 | 149 | def run(self, dataOut, minHei=None, maxHei=None, minIndex=None, maxIndex=None): |
|
|
150 | 150 | """ |
|
|
151 | 151 | Selecciona un bloque de datos en base a un grupo de valores de alturas segun el rango |
|
|
152 | 152 | minHei <= height <= maxHei |
|
|
153 | 153 | |
|
|
154 | 154 | Input: |
|
|
155 | 155 | minHei : valor minimo de altura a considerar |
|
|
156 | 156 | maxHei : valor maximo de altura a considerar |
|
|
157 | 157 | |
|
|
158 | 158 | Affected: |
|
|
159 | 159 | Indirectamente son cambiados varios valores a travez del metodo selectHeightsByIndex |
|
|
160 | 160 | |
|
|
161 | 161 | Return: |
|
|
162 | 162 | 1 si el metodo se ejecuto con exito caso contrario devuelve 0 |
|
|
163 | 163 | """ |
|
|
164 | 164 | |
|
|
165 | 165 | self.dataOut = dataOut |
|
|
166 | 166 | |
|
|
167 | 167 | if minHei and maxHei: |
|
|
168 | 168 | |
|
|
169 | 169 | if (minHei < self.dataOut.heightList[0]): |
|
|
170 | 170 | minHei = self.dataOut.heightList[0] |
|
|
171 | 171 | |
|
|
172 | 172 | if (maxHei > self.dataOut.heightList[-1]): |
|
|
173 | 173 | maxHei = self.dataOut.heightList[-1] |
|
|
174 | 174 | |
|
|
175 | 175 | minIndex = 0 |
|
|
176 | 176 | maxIndex = 0 |
|
|
177 | 177 | heights = self.dataOut.heightList |
|
|
178 | 178 | |
|
|
179 | 179 | inda = numpy.where(heights >= minHei) |
|
|
180 | 180 | indb = numpy.where(heights <= maxHei) |
|
|
181 | 181 | |
|
|
182 | 182 | try: |
|
|
183 | 183 | minIndex = inda[0][0] |
|
|
184 | 184 | except: |
|
|
185 | 185 | minIndex = 0 |
|
|
186 | 186 | |
|
|
187 | 187 | try: |
|
|
188 | 188 | maxIndex = indb[0][-1] |
|
|
189 | 189 | except: |
|
|
190 | 190 | maxIndex = len(heights) |
|
|
191 | 191 | |
|
|
192 | 192 | self.selectHeightsByIndex(minIndex, maxIndex) |
|
|
193 | 193 | |
|
|
194 | 194 | return self.dataOut |
|
|
195 | 195 | |
|
|
196 | 196 | def selectHeightsByIndex(self, minIndex, maxIndex): |
|
|
197 | 197 | """ |
|
|
198 | 198 | Selecciona un bloque de datos en base a un grupo indices de alturas segun el rango |
|
|
199 | 199 | minIndex <= index <= maxIndex |
|
|
200 | 200 | |
|
|
201 | 201 | Input: |
|
|
202 | 202 | minIndex : valor de indice minimo de altura a considerar |
|
|
203 | 203 | maxIndex : valor de indice maximo de altura a considerar |
|
|
204 | 204 | |
|
|
205 | 205 | Affected: |
|
|
206 | 206 | self.dataOut.data |
|
|
207 | 207 | self.dataOut.heightList |
|
|
208 | 208 | |
|
|
209 | 209 | Return: |
|
|
210 | 210 | 1 si el metodo se ejecuto con exito caso contrario devuelve 0 |
|
|
211 | 211 | """ |
|
|
212 | 212 | |
|
|
213 | 213 | if self.dataOut.type == 'Voltage': |
|
|
214 | 214 | if (minIndex < 0) or (minIndex > maxIndex): |
|
|
215 | 215 | raise ValueError("Height index range (%d,%d) is not valid" % (minIndex, maxIndex)) |
|
|
216 | 216 | |
|
|
217 | 217 | if (maxIndex >= self.dataOut.nHeights): |
|
|
218 | 218 | maxIndex = self.dataOut.nHeights |
|
|
219 | 219 | #print("shapeeee",self.dataOut.data.shape) |
|
|
220 | 220 | #voltage |
|
|
221 | 221 | if self.dataOut.flagDataAsBlock: |
|
|
222 | 222 | """ |
|
|
223 | 223 | Si la data es obtenida por bloques, dimension = [nChannels, nProfiles, nHeis] |
|
|
224 | 224 | """ |
|
|
225 | 225 | data = self.dataOut.data[:,:, minIndex:maxIndex] |
|
|
226 | 226 | else: |
|
|
227 | 227 | data = self.dataOut.data[:, minIndex:maxIndex] |
|
|
228 | 228 | |
|
|
229 | 229 | # firstHeight = self.dataOut.heightList[minIndex] |
|
|
230 | 230 | |
|
|
231 | 231 | self.dataOut.data = data |
|
|
232 | 232 | self.dataOut.heightList = self.dataOut.heightList[minIndex:maxIndex] |
|
|
233 | 233 | |
|
|
234 | 234 | if self.dataOut.nHeights <= 1: |
|
|
235 | 235 | raise ValueError("selectHeights: Too few heights. Current number of heights is %d" %(self.dataOut.nHeights)) |
|
|
236 | 236 | elif self.dataOut.type == 'Spectra': |
|
|
237 | 237 | if (minIndex < 0) or (minIndex > maxIndex): |
|
|
238 | 238 | raise ValueError("Error selecting heights: Index range (%d,%d) is not valid" % ( |
|
|
239 | 239 | minIndex, maxIndex)) |
|
|
240 | 240 | |
|
|
241 | 241 | if (maxIndex >= self.dataOut.nHeights): |
|
|
242 | 242 | maxIndex = self.dataOut.nHeights - 1 |
|
|
243 | 243 | |
|
|
244 | 244 | # Spectra |
|
|
245 | 245 | data_spc = self.dataOut.data_spc[:, :, minIndex:maxIndex + 1] |
|
|
246 | 246 | |
|
|
247 | 247 | data_cspc = None |
|
|
248 | 248 | if self.dataOut.data_cspc is not None: |
|
|
249 | 249 | data_cspc = self.dataOut.data_cspc[:, :, minIndex:maxIndex + 1] |
|
|
250 | 250 | |
|
|
251 | 251 | data_dc = None |
|
|
252 | 252 | if self.dataOut.data_dc is not None: |
|
|
253 | 253 | data_dc = self.dataOut.data_dc[:, minIndex:maxIndex + 1] |
|
|
254 | 254 | |
|
|
255 | 255 | self.dataOut.data_spc = data_spc |
|
|
256 | 256 | self.dataOut.data_cspc = data_cspc |
|
|
257 | 257 | self.dataOut.data_dc = data_dc |
|
|
258 | 258 | |
|
|
259 | 259 | self.dataOut.heightList = self.dataOut.heightList[minIndex:maxIndex + 1] |
|
|
260 | 260 | |
|
|
261 | 261 | return 1 |
|
|
262 | 262 | |
|
|
263 | 263 | |
|
|
264 | 264 | class filterByHeights(Operation): |
|
|
265 | 265 | |
|
|
266 | 266 | def run(self, dataOut, window): |
|
|
267 | 267 | |
|
|
268 | 268 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] |
|
|
269 | 269 | |
|
|
270 | 270 | if window == None: |
|
|
271 | 271 | window = (dataOut.radarControllerHeaderObj.txA/dataOut.radarControllerHeaderObj.nBaud) / deltaHeight |
|
|
272 | 272 | |
|
|
273 | 273 | newdelta = deltaHeight * window |
|
|
274 | 274 | r = dataOut.nHeights % window |
|
|
275 | 275 | newheights = (dataOut.nHeights-r)/window |
|
|
276 | 276 | |
|
|
277 | 277 | if newheights <= 1: |
|
|
278 | 278 | raise ValueError("filterByHeights: Too few heights. Current number of heights is %d and window is %d" %(dataOut.nHeights, window)) |
|
|
279 | 279 | |
|
|
280 | 280 | if dataOut.flagDataAsBlock: |
|
|
281 | 281 | """ |
|
|
282 | 282 | Si la data es obtenida por bloques, dimension = [nChannels, nProfiles, nHeis] |
|
|
283 | 283 | """ |
|
|
284 | 284 | buffer = dataOut.data[:, :, 0:int(dataOut.nHeights-r)] |
|
|
285 | 285 | buffer = buffer.reshape(dataOut.nChannels, dataOut.nProfiles, int(dataOut.nHeights/window), window) |
|
|
286 | 286 | buffer = numpy.sum(buffer,3) |
|
|
287 | 287 | |
|
|
288 | 288 | else: |
|
|
289 | 289 | buffer = dataOut.data[:,0:int(dataOut.nHeights-r)] |
|
|
290 | 290 | buffer = buffer.reshape(dataOut.nChannels,int(dataOut.nHeights/window),int(window)) |
|
|
291 | 291 | buffer = numpy.sum(buffer,2) |
|
|
292 | 292 | |
|
|
293 | 293 | dataOut.data = buffer |
|
|
294 | 294 | dataOut.heightList = dataOut.heightList[0] + numpy.arange( newheights )*newdelta |
|
|
295 | 295 | dataOut.windowOfFilter = window |
|
|
296 | 296 | |
|
|
297 | 297 | return dataOut |
|
|
298 | 298 | |
|
|
299 | 299 | |
|
|
300 | 300 | class setH0(Operation): |
|
|
301 | 301 | |
|
|
302 | 302 | def run(self, dataOut, h0, deltaHeight = None): |
|
|
303 | 303 | |
|
|
304 | 304 | if not deltaHeight: |
|
|
305 | 305 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] |
|
|
306 | 306 | |
|
|
307 | 307 | nHeights = dataOut.nHeights |
|
|
308 | 308 | |
|
|
309 | 309 | newHeiRange = h0 + numpy.arange(nHeights)*deltaHeight |
|
|
310 | 310 | |
|
|
311 | 311 | dataOut.heightList = newHeiRange |
|
|
312 | 312 | |
|
|
313 | 313 | return dataOut |
|
|
314 | 314 | |
|
|
315 | 315 | |
|
|
316 | 316 | class deFlip(Operation): |
|
|
317 | 317 | |
|
|
318 | 318 | def run(self, dataOut, channelList = []): |
|
|
319 | 319 | |
|
|
320 | 320 | data = dataOut.data.copy() |
|
|
321 | 321 | |
|
|
322 | 322 | if dataOut.flagDataAsBlock: |
|
|
323 | 323 | flip = self.flip |
|
|
324 | 324 | profileList = list(range(dataOut.nProfiles)) |
|
|
325 | 325 | |
|
|
326 | 326 | if not channelList: |
|
|
327 | 327 | for thisProfile in profileList: |
|
|
328 | 328 | data[:,thisProfile,:] = data[:,thisProfile,:]*flip |
|
|
329 | 329 | flip *= -1.0 |
|
|
330 | 330 | else: |
|
|
331 | 331 | for thisChannel in channelList: |
|
|
332 | 332 | if thisChannel not in dataOut.channelList: |
|
|
333 | 333 | continue |
|
|
334 | 334 | |
|
|
335 | 335 | for thisProfile in profileList: |
|
|
336 | 336 | data[thisChannel,thisProfile,:] = data[thisChannel,thisProfile,:]*flip |
|
|
337 | 337 | flip *= -1.0 |
|
|
338 | 338 | |
|
|
339 | 339 | self.flip = flip |
|
|
340 | 340 | |
|
|
341 | 341 | else: |
|
|
342 | 342 | if not channelList: |
|
|
343 | 343 | data[:,:] = data[:,:]*self.flip |
|
|
344 | 344 | else: |
|
|
345 | 345 | for thisChannel in channelList: |
|
|
346 | 346 | if thisChannel not in dataOut.channelList: |
|
|
347 | 347 | continue |
|
|
348 | 348 | |
|
|
349 | 349 | data[thisChannel,:] = data[thisChannel,:]*self.flip |
|
|
350 | 350 | |
|
|
351 | 351 | self.flip *= -1. |
|
|
352 | 352 | |
|
|
353 | 353 | dataOut.data = data |
|
|
354 | 354 | |
|
|
355 | 355 | return dataOut |
|
|
356 | 356 | |
|
|
357 | 357 | |
|
|
358 | 358 | class setAttribute(Operation): |
|
|
359 | 359 | ''' |
|
|
360 | 360 | Set an arbitrary attribute(s) to dataOut |
|
|
361 | 361 | ''' |
|
|
362 | 362 | |
|
|
363 | 363 | def __init__(self): |
|
|
364 | 364 | |
|
|
365 | 365 | Operation.__init__(self) |
|
|
366 | 366 | self._ready = False |
|
|
367 | 367 | |
|
|
368 | 368 | def run(self, dataOut, **kwargs): |
|
|
369 | 369 | |
|
|
370 | 370 | for key, value in kwargs.items(): |
|
|
371 | 371 | setattr(dataOut, key, value) |
|
|
372 | 372 | |
|
|
373 | 373 | return dataOut |
|
|
374 | 374 | |
|
|
375 | 375 | |
|
|
376 | 376 | @MPDecorator |
|
|
377 | 377 | class printAttribute(Operation): |
|
|
378 | 378 | ''' |
|
|
379 | 379 | Print an arbitrary attribute of dataOut |
|
|
380 | 380 | ''' |
|
|
381 | 381 | |
|
|
382 | 382 | def __init__(self): |
|
|
383 | 383 | |
|
|
384 | 384 | Operation.__init__(self) |
|
|
385 | 385 | |
|
|
386 | 386 | def run(self, dataOut, attributes): |
|
|
387 | 387 | |
|
|
388 | 388 | if isinstance(attributes, str): |
|
|
389 | 389 | attributes = [attributes] |
|
|
390 | 390 | for attr in attributes: |
|
|
391 | 391 | if hasattr(dataOut, attr): |
|
|
392 | 392 | log.log(getattr(dataOut, attr), attr) |
|
|
393 | 393 | |
|
|
394 | 394 | |
|
|
395 | 395 | class interpolateHeights(Operation): |
|
|
396 | 396 | |
|
|
397 | 397 | def run(self, dataOut, topLim, botLim): |
|
|
398 | 398 | #69 al 72 para julia |
|
|
399 | 399 | #82-84 para meteoros |
|
|
400 | 400 | if len(numpy.shape(dataOut.data))==2: |
|
|
401 | 401 | sampInterp = (dataOut.data[:,botLim-1] + dataOut.data[:,topLim+1])/2 |
|
|
402 | 402 | sampInterp = numpy.transpose(numpy.tile(sampInterp,(topLim-botLim + 1,1))) |
|
|
403 | 403 | #dataOut.data[:,botLim:limSup+1] = sampInterp |
|
|
404 | 404 | dataOut.data[:,botLim:topLim+1] = sampInterp |
|
|
405 | 405 | else: |
|
|
406 | 406 | nHeights = dataOut.data.shape[2] |
|
|
407 | 407 | x = numpy.hstack((numpy.arange(botLim),numpy.arange(topLim+1,nHeights))) |
|
|
408 | 408 | y = dataOut.data[:,:,list(range(botLim))+list(range(topLim+1,nHeights))] |
|
|
409 | 409 | f = interpolate.interp1d(x, y, axis = 2) |
|
|
410 | 410 | xnew = numpy.arange(botLim,topLim+1) |
|
|
411 | 411 | ynew = f(xnew) |
|
|
412 | 412 | dataOut.data[:,:,botLim:topLim+1] = ynew |
|
|
413 | 413 | |
|
|
414 | 414 | return dataOut |
|
|
415 | 415 | |
|
|
416 | 416 | |
|
|
417 | 417 | class CohInt(Operation): |
|
|
418 | 418 | |
|
|
419 | 419 | isConfig = False |
|
|
420 | 420 | __profIndex = 0 |
|
|
421 | 421 | __byTime = False |
|
|
422 | 422 | __initime = None |
|
|
423 | 423 | __lastdatatime = None |
|
|
424 | 424 | __integrationtime = None |
|
|
425 | 425 | __buffer = None |
|
|
426 | 426 | __bufferStride = [] |
|
|
427 | 427 | __dataReady = False |
|
|
428 | 428 | __profIndexStride = 0 |
|
|
429 | 429 | __dataToPutStride = False |
|
|
430 | 430 | n = None |
|
|
431 | 431 | |
|
|
432 | 432 | def __init__(self, **kwargs): |
|
|
433 | 433 | |
|
|
434 | 434 | Operation.__init__(self, **kwargs) |
|
|
435 | 435 | |
|
|
436 | 436 | def setup(self, n=None, timeInterval=None, stride=None, overlapping=False, byblock=False): |
|
|
437 | 437 | """ |
|
|
438 | 438 | Set the parameters of the integration class. |
|
|
439 | 439 | |
|
|
440 | 440 | Inputs: |
|
|
441 | 441 | |
|
|
442 | 442 | n : Number of coherent integrations |
|
|
443 | 443 | timeInterval : Time of integration. If the parameter "n" is selected this one does not work |
|
|
444 | 444 | overlapping : |
|
|
445 | 445 | """ |
|
|
446 | 446 | |
|
|
447 | 447 | self.__initime = None |
|
|
448 | 448 | self.__lastdatatime = 0 |
|
|
449 | 449 | self.__buffer = None |
|
|
450 | 450 | self.__dataReady = False |
|
|
451 | 451 | self.byblock = byblock |
|
|
452 | 452 | self.stride = stride |
|
|
453 | 453 | |
|
|
454 | 454 | if n == None and timeInterval == None: |
|
|
455 | 455 | raise ValueError("n or timeInterval should be specified ...") |
|
|
456 | 456 | |
|
|
457 | 457 | if n != None: |
|
|
458 | 458 | self.n = n |
|
|
459 | 459 | self.__byTime = False |
|
|
460 | 460 | else: |
|
|
461 | 461 | self.__integrationtime = timeInterval #* 60. #if (type(timeInterval)!=integer) -> change this line |
|
|
462 | 462 | self.n = 9999 |
|
|
463 | 463 | self.__byTime = True |
|
|
464 | 464 | |
|
|
465 | 465 | if overlapping: |
|
|
466 | 466 | self.__withOverlapping = True |
|
|
467 | 467 | self.__buffer = None |
|
|
468 | 468 | else: |
|
|
469 | 469 | self.__withOverlapping = False |
|
|
470 | 470 | self.__buffer = 0 |
|
|
471 | 471 | |
|
|
472 | 472 | self.__profIndex = 0 |
|
|
473 | 473 | |
|
|
474 | 474 | def putData(self, data): |
|
|
475 | 475 | |
|
|
476 | 476 | """ |
|
|
477 | 477 | Add a profile to the __buffer and increase in one the __profileIndex |
|
|
478 | 478 | |
|
|
479 | 479 | """ |
|
|
480 | 480 | |
|
|
481 | 481 | if not self.__withOverlapping: |
|
|
482 | 482 | self.__buffer += data.copy() |
|
|
483 | 483 | self.__profIndex += 1 |
|
|
484 | 484 | return |
|
|
485 | 485 | |
|
|
486 | 486 | #Overlapping data |
|
|
487 | 487 | nChannels, nHeis = data.shape |
|
|
488 | 488 | data = numpy.reshape(data, (1, nChannels, nHeis)) |
|
|
489 | 489 | |
|
|
490 | 490 | #If the buffer is empty then it takes the data value |
|
|
491 | 491 | if self.__buffer is None: |
|
|
492 | 492 | self.__buffer = data |
|
|
493 | 493 | self.__profIndex += 1 |
|
|
494 | 494 | return |
|
|
495 | 495 | |
|
|
496 | 496 | #If the buffer length is lower than n then stakcing the data value |
|
|
497 | 497 | if self.__profIndex < self.n: |
|
|
498 | 498 | self.__buffer = numpy.vstack((self.__buffer, data)) |
|
|
499 | 499 | self.__profIndex += 1 |
|
|
500 | 500 | return |
|
|
501 | 501 | |
|
|
502 | 502 | #If the buffer length is equal to n then replacing the last buffer value with the data value |
|
|
503 | 503 | self.__buffer = numpy.roll(self.__buffer, -1, axis=0) |
|
|
504 | 504 | self.__buffer[self.n-1] = data |
|
|
505 | 505 | self.__profIndex = self.n |
|
|
506 | 506 | return |
|
|
507 | 507 | |
|
|
508 | 508 | |
|
|
509 | 509 | def pushData(self): |
|
|
510 | 510 | """ |
|
|
511 | 511 | Return the sum of the last profiles and the profiles used in the sum. |
|
|
512 | 512 | |
|
|
513 | 513 | Affected: |
|
|
514 | 514 | |
|
|
515 | 515 | self.__profileIndex |
|
|
516 | 516 | |
|
|
517 | 517 | """ |
|
|
518 | 518 | |
|
|
519 | 519 | if not self.__withOverlapping: |
|
|
520 | 520 | data = self.__buffer |
|
|
521 | 521 | n = self.__profIndex |
|
|
522 | 522 | |
|
|
523 | 523 | self.__buffer = 0 |
|
|
524 | 524 | self.__profIndex = 0 |
|
|
525 | 525 | |
|
|
526 | 526 | return data, n |
|
|
527 | 527 | |
|
|
528 | 528 | #Integration with Overlapping |
|
|
529 | 529 | data = numpy.sum(self.__buffer, axis=0) |
|
|
530 | 530 | # print data |
|
|
531 | 531 | # raise |
|
|
532 | 532 | n = self.__profIndex |
|
|
533 | 533 | |
|
|
534 | 534 | return data, n |
|
|
535 | 535 | |
|
|
536 | 536 | def byProfiles(self, data): |
|
|
537 | 537 | |
|
|
538 | 538 | self.__dataReady = False |
|
|
539 | 539 | avgdata = None |
|
|
540 | 540 | # n = None |
|
|
541 | 541 | # print data |
|
|
542 | 542 | # raise |
|
|
543 | 543 | self.putData(data) |
|
|
544 | 544 | |
|
|
545 | 545 | if self.__profIndex == self.n: |
|
|
546 | 546 | avgdata, n = self.pushData() |
|
|
547 | 547 | self.__dataReady = True |
|
|
548 | 548 | |
|
|
549 | 549 | return avgdata |
|
|
550 | 550 | |
|
|
551 | 551 | def byTime(self, data, datatime): |
|
|
552 | 552 | |
|
|
553 | 553 | self.__dataReady = False |
|
|
554 | 554 | avgdata = None |
|
|
555 | 555 | n = None |
|
|
556 | 556 | |
|
|
557 | 557 | self.putData(data) |
|
|
558 | 558 | |
|
|
559 | 559 | if (datatime - self.__initime) >= self.__integrationtime: |
|
|
560 | 560 | avgdata, n = self.pushData() |
|
|
561 | 561 | self.n = n |
|
|
562 | 562 | self.__dataReady = True |
|
|
563 | 563 | |
|
|
564 | 564 | return avgdata |
|
|
565 | 565 | |
|
|
566 | 566 | def integrateByStride(self, data, datatime): |
|
|
567 | 567 | # print data |
|
|
568 | 568 | if self.__profIndex == 0: |
|
|
569 | 569 | self.__buffer = [[data.copy(), datatime]] |
|
|
570 | 570 | else: |
|
|
571 | 571 | self.__buffer.append([data.copy(),datatime]) |
|
|
572 | 572 | self.__profIndex += 1 |
|
|
573 | 573 | self.__dataReady = False |
|
|
574 | 574 | |
|
|
575 | 575 | if self.__profIndex == self.n * self.stride : |
|
|
576 | 576 | self.__dataToPutStride = True |
|
|
577 | 577 | self.__profIndexStride = 0 |
|
|
578 | 578 | self.__profIndex = 0 |
|
|
579 | 579 | self.__bufferStride = [] |
|
|
580 | 580 | for i in range(self.stride): |
|
|
581 | 581 | current = self.__buffer[i::self.stride] |
|
|
582 | 582 | data = numpy.sum([t[0] for t in current], axis=0) |
|
|
583 | 583 | avgdatatime = numpy.average([t[1] for t in current]) |
|
|
584 | 584 | # print data |
|
|
585 | 585 | self.__bufferStride.append((data, avgdatatime)) |
|
|
586 | 586 | |
|
|
587 | 587 | if self.__dataToPutStride: |
|
|
588 | 588 | self.__dataReady = True |
|
|
589 | 589 | self.__profIndexStride += 1 |
|
|
590 | 590 | if self.__profIndexStride == self.stride: |
|
|
591 | 591 | self.__dataToPutStride = False |
|
|
592 | 592 | # print self.__bufferStride[self.__profIndexStride - 1] |
|
|
593 | 593 | # raise |
|
|
594 | 594 | return self.__bufferStride[self.__profIndexStride - 1] |
|
|
595 | 595 | |
|
|
596 | 596 | |
|
|
597 | 597 | return None, None |
|
|
598 | 598 | |
|
|
599 | 599 | def integrate(self, data, datatime=None): |
|
|
600 | 600 | |
|
|
601 | 601 | if self.__initime == None: |
|
|
602 | 602 | self.__initime = datatime |
|
|
603 | 603 | |
|
|
604 | 604 | if self.__byTime: |
|
|
605 | 605 | avgdata = self.byTime(data, datatime) |
|
|
606 | 606 | else: |
|
|
607 | 607 | avgdata = self.byProfiles(data) |
|
|
608 | 608 | |
|
|
609 | 609 | |
|
|
610 | 610 | self.__lastdatatime = datatime |
|
|
611 | 611 | |
|
|
612 | 612 | if avgdata is None: |
|
|
613 | 613 | return None, None |
|
|
614 | 614 | |
|
|
615 | 615 | avgdatatime = self.__initime |
|
|
616 | 616 | |
|
|
617 | 617 | deltatime = datatime - self.__lastdatatime |
|
|
618 | 618 | |
|
|
619 | 619 | if not self.__withOverlapping: |
|
|
620 | 620 | self.__initime = datatime |
|
|
621 | 621 | else: |
|
|
622 | 622 | self.__initime += deltatime |
|
|
623 | 623 | |
|
|
624 | 624 | return avgdata, avgdatatime |
|
|
625 | 625 | |
|
|
626 | 626 | def integrateByBlock(self, dataOut): |
|
|
627 | 627 | |
|
|
628 | 628 | times = int(dataOut.data.shape[1]/self.n) |
|
|
629 | 629 | avgdata = numpy.zeros((dataOut.nChannels, times, dataOut.nHeights), dtype=numpy.complex) |
|
|
630 | 630 | |
|
|
631 | 631 | id_min = 0 |
|
|
632 | 632 | id_max = self.n |
|
|
633 | 633 | |
|
|
634 | 634 | for i in range(times): |
|
|
635 | 635 | junk = dataOut.data[:,id_min:id_max,:] |
|
|
636 | 636 | avgdata[:,i,:] = junk.sum(axis=1) |
|
|
637 | 637 | id_min += self.n |
|
|
638 | 638 | id_max += self.n |
|
|
639 | 639 | |
|
|
640 | 640 | timeInterval = dataOut.ippSeconds*self.n |
|
|
641 | 641 | avgdatatime = (times - 1) * timeInterval + dataOut.utctime |
|
|
642 | 642 | self.__dataReady = True |
|
|
643 | 643 | return avgdata, avgdatatime |
|
|
644 | 644 | |
|
|
645 | 645 | def run(self, dataOut, n=None, timeInterval=None, stride=None, overlapping=False, byblock=False, **kwargs): |
|
|
646 | 646 | |
|
|
647 | 647 | if not self.isConfig: |
|
|
648 | 648 | self.setup(n=n, stride=stride, timeInterval=timeInterval, overlapping=overlapping, byblock=byblock, **kwargs) |
|
|
649 | 649 | self.isConfig = True |
|
|
650 | 650 | |
|
|
651 | 651 | if dataOut.flagDataAsBlock: |
|
|
652 | 652 | """ |
|
|
653 | 653 | Si la data es leida por bloques, dimension = [nChannels, nProfiles, nHeis] |
|
|
654 | 654 | """ |
|
|
655 | 655 | avgdata, avgdatatime = self.integrateByBlock(dataOut) |
|
|
656 | 656 | dataOut.nProfiles /= self.n |
|
|
657 | 657 | else: |
|
|
658 | 658 | if stride is None: |
|
|
659 | 659 | avgdata, avgdatatime = self.integrate(dataOut.data, dataOut.utctime) |
|
|
660 | 660 | else: |
|
|
661 | 661 | avgdata, avgdatatime = self.integrateByStride(dataOut.data, dataOut.utctime) |
|
|
662 | 662 | |
|
|
663 | 663 | |
|
|
664 | 664 | # dataOut.timeInterval *= n |
|
|
665 | 665 | dataOut.flagNoData = True |
|
|
666 | 666 | |
|
|
667 | 667 | if self.__dataReady: |
|
|
668 | 668 | dataOut.data = avgdata |
|
|
669 | 669 | if not dataOut.flagCohInt: |
|
|
670 | 670 | dataOut.nCohInt *= self.n |
|
|
671 | 671 | dataOut.flagCohInt = True |
|
|
672 | 672 | dataOut.utctime = avgdatatime |
|
|
673 | 673 | # print avgdata, avgdatatime |
|
|
674 | 674 | # raise |
|
|
675 | 675 | # dataOut.timeInterval = dataOut.ippSeconds * dataOut.nCohInt |
|
|
676 | 676 | dataOut.flagNoData = False |
|
|
677 | 677 | return dataOut |
|
|
678 | 678 | |
|
|
679 | 679 | class Decoder(Operation): |
|
|
680 | 680 | |
|
|
681 | 681 | isConfig = False |
|
|
682 | 682 | __profIndex = 0 |
|
|
683 | 683 | |
|
|
684 | 684 | code = None |
|
|
685 | 685 | |
|
|
686 | 686 | nCode = None |
|
|
687 | 687 | nBaud = None |
|
|
688 | 688 | |
|
|
689 | 689 | def __init__(self, **kwargs): |
|
|
690 | 690 | |
|
|
691 | 691 | Operation.__init__(self, **kwargs) |
|
|
692 | 692 | |
|
|
693 | 693 | self.times = None |
|
|
694 | 694 | self.osamp = None |
|
|
695 | 695 | # self.__setValues = False |
|
|
696 | 696 | self.isConfig = False |
|
|
697 | 697 | self.setupReq = False |
|
|
698 | 698 | def setup(self, code, osamp, dataOut): |
|
|
699 | 699 | |
|
|
700 | 700 | self.__profIndex = 0 |
|
|
701 | 701 | |
|
|
702 | 702 | self.code = code |
|
|
703 | 703 | |
|
|
704 | 704 | self.nCode = len(code) |
|
|
705 | 705 | self.nBaud = len(code[0]) |
|
|
706 | 706 | |
|
|
707 | 707 | if (osamp != None) and (osamp >1): |
|
|
708 | 708 | self.osamp = osamp |
|
|
709 | 709 | self.code = numpy.repeat(code, repeats=self.osamp, axis=1) |
|
|
710 | 710 | self.nBaud = self.nBaud*self.osamp |
|
|
711 | 711 | |
|
|
712 | 712 | self.__nChannels = dataOut.nChannels |
|
|
713 | 713 | self.__nProfiles = dataOut.nProfiles |
|
|
714 | 714 | self.__nHeis = dataOut.nHeights |
|
|
715 | 715 | |
|
|
716 | 716 | if self.__nHeis < self.nBaud: |
|
|
717 | 717 | raise ValueError('Number of heights (%d) should be greater than number of bauds (%d)' %(self.__nHeis, self.nBaud)) |
|
|
718 | 718 | |
|
|
719 | 719 | #Frequency |
|
|
720 | 720 | __codeBuffer = numpy.zeros((self.nCode, self.__nHeis), dtype=numpy.complex) |
|
|
721 | 721 | |
|
|
722 | 722 | __codeBuffer[:,0:self.nBaud] = self.code |
|
|
723 | 723 | |
|
|
724 | 724 | self.fft_code = numpy.conj(numpy.fft.fft(__codeBuffer, axis=1)) |
|
|
725 | 725 | |
|
|
726 | 726 | if dataOut.flagDataAsBlock: |
|
|
727 | 727 | |
|
|
728 | 728 | self.ndatadec = self.__nHeis #- self.nBaud + 1 |
|
|
729 | 729 | |
|
|
730 | 730 | self.datadecTime = numpy.zeros((self.__nChannels, self.__nProfiles, self.ndatadec), dtype=numpy.complex) |
|
|
731 | 731 | |
|
|
732 | 732 | else: |
|
|
733 | 733 | |
|
|
734 | 734 | #Time |
|
|
735 | 735 | self.ndatadec = self.__nHeis #- self.nBaud + 1 |
|
|
736 | 736 | |
|
|
737 | 737 | self.datadecTime = numpy.zeros((self.__nChannels, self.ndatadec), dtype=numpy.complex) |
|
|
738 | 738 | |
|
|
739 | 739 | def __convolutionInFreq(self, data): |
|
|
740 | 740 | |
|
|
741 | 741 | fft_code = self.fft_code[self.__profIndex].reshape(1,-1) |
|
|
742 | 742 | |
|
|
743 | 743 | fft_data = numpy.fft.fft(data, axis=1) |
|
|
744 | 744 | |
|
|
745 | 745 | conv = fft_data*fft_code |
|
|
746 | 746 | |
|
|
747 | 747 | data = numpy.fft.ifft(conv,axis=1) |
|
|
748 | 748 | |
|
|
749 | 749 | return data |
|
|
750 | 750 | |
|
|
751 | 751 | def __convolutionInFreqOpt(self, data): |
|
|
752 | 752 | |
|
|
753 | 753 | raise NotImplementedError |
|
|
754 | 754 | |
|
|
755 | 755 | def __convolutionInTime(self, data): |
|
|
756 | 756 | |
|
|
757 | 757 | code = self.code[self.__profIndex] |
|
|
758 | 758 | for i in range(self.__nChannels): |
|
|
759 | 759 | self.datadecTime[i,:] = numpy.correlate(data[i,:], code, mode='full')[self.nBaud-1:] |
|
|
760 | 760 | |
|
|
761 | 761 | return self.datadecTime |
|
|
762 | 762 | |
|
|
763 | 763 | def __convolutionByBlockInTime(self, data): |
|
|
764 | 764 | |
|
|
765 | 765 | repetitions = int(self.__nProfiles / self.nCode) |
|
|
766 | 766 | junk = numpy.lib.stride_tricks.as_strided(self.code, (repetitions, self.code.size), (0, self.code.itemsize)) |
|
|
767 | 767 | junk = junk.flatten() |
|
|
768 | 768 | code_block = numpy.reshape(junk, (self.nCode*repetitions, self.nBaud)) |
|
|
769 | 769 | profilesList = range(self.__nProfiles) |
|
|
770 | 770 | |
|
|
771 | 771 | for i in range(self.__nChannels): |
|
|
772 | 772 | for j in profilesList: |
|
|
773 | 773 | self.datadecTime[i,j,:] = numpy.correlate(data[i,j,:], code_block[j,:], mode='full')[self.nBaud-1:] |
|
|
774 | 774 | return self.datadecTime |
|
|
775 | 775 | |
|
|
776 | 776 | def __convolutionByBlockInFreq(self, data): |
|
|
777 | 777 | |
|
|
778 | 778 | raise NotImplementedError("Decoder by frequency fro Blocks not implemented") |
|
|
779 | 779 | |
|
|
780 | 780 | |
|
|
781 | 781 | fft_code = self.fft_code[self.__profIndex].reshape(1,-1) |
|
|
782 | 782 | |
|
|
783 | 783 | fft_data = numpy.fft.fft(data, axis=2) |
|
|
784 | 784 | |
|
|
785 | 785 | conv = fft_data*fft_code |
|
|
786 | 786 | |
|
|
787 | 787 | data = numpy.fft.ifft(conv,axis=2) |
|
|
788 | 788 | |
|
|
789 | 789 | return data |
|
|
790 | 790 | |
|
|
791 | 791 | |
|
|
792 | 792 | def run(self, dataOut, code=None, nCode=None, nBaud=None, mode = 0, osamp=None, times=None): |
|
|
793 | 793 | |
|
|
794 | 794 | if dataOut.flagDecodeData: |
|
|
795 | 795 | print("This data is already decoded, recoding again ...") |
|
|
796 | 796 | |
|
|
797 | 797 | if not self.isConfig: |
|
|
798 | 798 | |
|
|
799 | 799 | if code is None: |
|
|
800 | 800 | if dataOut.code is None: |
|
|
801 | 801 | raise ValueError("Code could not be read from %s instance. Enter a value in Code parameter" %dataOut.type) |
|
|
802 | 802 | |
|
|
803 | 803 | code = dataOut.code |
|
|
804 | 804 | else: |
|
|
805 | 805 | code = numpy.array(code).reshape(nCode,nBaud) |
|
|
806 | 806 | self.setup(code, osamp, dataOut) |
|
|
807 | 807 | |
|
|
808 | 808 | self.isConfig = True |
|
|
809 | 809 | |
|
|
810 | 810 | if mode == 3: |
|
|
811 | 811 | sys.stderr.write("Decoder Warning: mode=%d is not valid, using mode=0\n" %mode) |
|
|
812 | 812 | |
|
|
813 | 813 | if times != None: |
|
|
814 | 814 | sys.stderr.write("Decoder Warning: Argument 'times' in not used anymore\n") |
|
|
815 | 815 | |
|
|
816 | 816 | if self.code is None: |
|
|
817 | 817 | print("Fail decoding: Code is not defined.") |
|
|
818 | 818 | return |
|
|
819 | 819 | |
|
|
820 | 820 | self.__nProfiles = dataOut.nProfiles |
|
|
821 | 821 | datadec = None |
|
|
822 | 822 | |
|
|
823 | 823 | if mode == 3: |
|
|
824 | 824 | mode = 0 |
|
|
825 | 825 | |
|
|
826 | 826 | if dataOut.flagDataAsBlock: |
|
|
827 | 827 | """ |
|
|
828 | 828 | Decoding when data have been read as block, |
|
|
829 | 829 | """ |
|
|
830 | 830 | |
|
|
831 | 831 | if mode == 0: |
|
|
832 | 832 | datadec = self.__convolutionByBlockInTime(dataOut.data) |
|
|
833 | 833 | if mode == 1: |
|
|
834 | 834 | datadec = self.__convolutionByBlockInFreq(dataOut.data) |
|
|
835 | 835 | else: |
|
|
836 | 836 | """ |
|
|
837 | 837 | Decoding when data have been read profile by profile |
|
|
838 | 838 | """ |
|
|
839 | 839 | if mode == 0: |
|
|
840 | 840 | datadec = self.__convolutionInTime(dataOut.data) |
|
|
841 | 841 | |
|
|
842 | 842 | if mode == 1: |
|
|
843 | 843 | datadec = self.__convolutionInFreq(dataOut.data) |
|
|
844 | 844 | |
|
|
845 | 845 | if mode == 2: |
|
|
846 | 846 | datadec = self.__convolutionInFreqOpt(dataOut.data) |
|
|
847 | 847 | |
|
|
848 | 848 | if datadec is None: |
|
|
849 | 849 | raise ValueError("Codification mode selected is not valid: mode=%d. Try selecting 0 or 1" %mode) |
|
|
850 | 850 | |
|
|
851 | 851 | dataOut.code = self.code |
|
|
852 | 852 | dataOut.nCode = self.nCode |
|
|
853 | 853 | dataOut.nBaud = self.nBaud |
|
|
854 | 854 | |
|
|
855 | 855 | dataOut.data = datadec |
|
|
856 | 856 | |
|
|
857 | 857 | dataOut.heightList = dataOut.heightList[0:datadec.shape[-1]] |
|
|
858 | 858 | |
|
|
859 | 859 | dataOut.flagDecodeData = True #asumo q la data esta decodificada |
|
|
860 | 860 | |
|
|
861 | 861 | if self.__profIndex == self.nCode-1: |
|
|
862 | 862 | self.__profIndex = 0 |
|
|
863 | 863 | return dataOut |
|
|
864 | 864 | |
|
|
865 | 865 | self.__profIndex += 1 |
|
|
866 | 866 | |
|
|
867 | 867 | return dataOut |
|
|
868 | 868 | # dataOut.flagDeflipData = True #asumo q la data no esta sin flip |
|
|
869 | 869 | |
|
|
870 | 870 | |
|
|
871 | 871 | class ProfileConcat(Operation): |
|
|
872 | 872 | |
|
|
873 | 873 | isConfig = False |
|
|
874 | 874 | buffer = None |
|
|
875 | 875 | |
|
|
876 | 876 | def __init__(self, **kwargs): |
|
|
877 | 877 | |
|
|
878 | 878 | Operation.__init__(self, **kwargs) |
|
|
879 | 879 | self.profileIndex = 0 |
|
|
880 | 880 | |
|
|
881 | 881 | def reset(self): |
|
|
882 | 882 | self.buffer = numpy.zeros_like(self.buffer) |
|
|
883 | 883 | self.start_index = 0 |
|
|
884 | 884 | self.times = 1 |
|
|
885 | 885 | |
|
|
886 | 886 | def setup(self, data, m, n=1): |
|
|
887 | 887 | self.buffer = numpy.zeros((data.shape[0],data.shape[1]*m),dtype=type(data[0,0])) |
|
|
888 | 888 | self.nHeights = data.shape[1]#.nHeights |
|
|
889 | 889 | self.start_index = 0 |
|
|
890 | 890 | self.times = 1 |
|
|
891 | 891 | |
|
|
892 | 892 | def concat(self, data): |
|
|
893 | 893 | |
|
|
894 | 894 | self.buffer[:,self.start_index:self.nHeights*self.times] = data.copy() |
|
|
895 | 895 | self.start_index = self.start_index + self.nHeights |
|
|
896 | 896 | |
|
|
897 | 897 | def run(self, dataOut, m): |
|
|
898 | 898 | dataOut.flagNoData = True |
|
|
899 | 899 | |
|
|
900 | 900 | if not self.isConfig: |
|
|
901 | 901 | self.setup(dataOut.data, m, 1) |
|
|
902 | 902 | self.isConfig = True |
|
|
903 | 903 | |
|
|
904 | 904 | if dataOut.flagDataAsBlock: |
|
|
905 | 905 | raise ValueError("ProfileConcat can only be used when voltage have been read profile by profile, getBlock = False") |
|
|
906 | 906 | |
|
|
907 | 907 | else: |
|
|
908 | 908 | self.concat(dataOut.data) |
|
|
909 | 909 | self.times += 1 |
|
|
910 | 910 | if self.times > m: |
|
|
911 | 911 | dataOut.data = self.buffer |
|
|
912 | 912 | self.reset() |
|
|
913 | 913 | dataOut.flagNoData = False |
|
|
914 | 914 | # se deben actualizar mas propiedades del header y del objeto dataOut, por ejemplo, las alturas |
|
|
915 | 915 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] |
|
|
916 | 916 | xf = dataOut.heightList[0] + dataOut.nHeights * deltaHeight * m |
|
|
917 | 917 | dataOut.heightList = numpy.arange(dataOut.heightList[0], xf, deltaHeight) |
|
|
918 | 918 | dataOut.ippSeconds *= m |
|
|
919 | 919 | return dataOut |
|
|
920 | 920 | |
|
|
921 | 921 | class ProfileSelector(Operation): |
|
|
922 | 922 | |
|
|
923 | 923 | profileIndex = None |
|
|
924 | 924 | # Tamanho total de los perfiles |
|
|
925 | 925 | nProfiles = None |
|
|
926 | 926 | |
|
|
927 | 927 | def __init__(self, **kwargs): |
|
|
928 | 928 | |
|
|
929 | 929 | Operation.__init__(self, **kwargs) |
|
|
930 | 930 | self.profileIndex = 0 |
|
|
931 | 931 | |
|
|
932 | 932 | def incProfileIndex(self): |
|
|
933 | 933 | |
|
|
934 | 934 | self.profileIndex += 1 |
|
|
935 | 935 | |
|
|
936 | 936 | if self.profileIndex >= self.nProfiles: |
|
|
937 | 937 | self.profileIndex = 0 |
|
|
938 | 938 | |
|
|
939 | 939 | def isThisProfileInRange(self, profileIndex, minIndex, maxIndex): |
|
|
940 | 940 | |
|
|
941 | 941 | if profileIndex < minIndex: |
|
|
942 | 942 | return False |
|
|
943 | 943 | |
|
|
944 | 944 | if profileIndex > maxIndex: |
|
|
945 | 945 | return False |
|
|
946 | 946 | |
|
|
947 | 947 | return True |
|
|
948 | 948 | |
|
|
949 | 949 | def isThisProfileInList(self, profileIndex, profileList): |
|
|
950 | 950 | |
|
|
951 | 951 | if profileIndex not in profileList: |
|
|
952 | 952 | return False |
|
|
953 | 953 | |
|
|
954 | 954 | return True |
|
|
955 | 955 | |
|
|
956 | 956 | def run(self, dataOut, profileList=None, profileRangeList=None, beam=None, byblock=False, rangeList = None, nProfiles=None): |
|
|
957 | ||
|
|
957 | #print("before",dataOut.data.shape) | |
|
|
958 | 958 | """ |
|
|
959 | 959 | ProfileSelector: |
|
|
960 | 960 | |
|
|
961 | 961 | Inputs: |
|
|
962 | 962 | profileList : Index of profiles selected. Example: profileList = (0,1,2,7,8) |
|
|
963 | 963 | |
|
|
964 | 964 | profileRangeList : Minimum and maximum profile indexes. Example: profileRangeList = (4, 30) |
|
|
965 | 965 | |
|
|
966 | 966 | rangeList : List of profile ranges. Example: rangeList = ((4, 30), (32, 64), (128, 256)) |
|
|
967 | 967 | |
|
|
968 | 968 | """ |
|
|
969 | 969 | |
|
|
970 | 970 | if rangeList is not None: |
|
|
971 | 971 | if type(rangeList[0]) not in (tuple, list): |
|
|
972 | 972 | rangeList = [rangeList] |
|
|
973 | 973 | |
|
|
974 | 974 | dataOut.flagNoData = True |
|
|
975 | 975 | |
|
|
976 | 976 | if dataOut.flagDataAsBlock: |
|
|
977 | 977 | """ |
|
|
978 | 978 | data dimension = [nChannels, nProfiles, nHeis] |
|
|
979 | 979 | """ |
|
|
980 | 980 | if profileList != None: |
|
|
981 | 981 | dataOut.data = dataOut.data[:,profileList,:] |
|
|
982 | 982 | |
|
|
983 | 983 | if profileRangeList != None: |
|
|
984 | 984 | minIndex = profileRangeList[0] |
|
|
985 | 985 | maxIndex = profileRangeList[1] |
|
|
986 | 986 | profileList = list(range(minIndex, maxIndex+1)) |
|
|
987 | 987 | |
|
|
988 | 988 | dataOut.data = dataOut.data[:,minIndex:maxIndex+1,:] |
|
|
989 | 989 | |
|
|
990 | 990 | if rangeList != None: |
|
|
991 | 991 | |
|
|
992 | 992 | profileList = [] |
|
|
993 | 993 | |
|
|
994 | 994 | for thisRange in rangeList: |
|
|
995 | 995 | minIndex = thisRange[0] |
|
|
996 | 996 | maxIndex = thisRange[1] |
|
|
997 | 997 | |
|
|
998 | 998 | profileList.extend(list(range(minIndex, maxIndex+1))) |
|
|
999 | 999 | |
|
|
1000 | 1000 | dataOut.data = dataOut.data[:,profileList,:] |
|
|
1001 | 1001 | |
|
|
1002 | 1002 | dataOut.nProfiles = len(profileList) |
|
|
1003 | 1003 | dataOut.profileIndex = dataOut.nProfiles - 1 |
|
|
1004 | 1004 | dataOut.flagNoData = False |
|
|
1005 | ||
|
|
1005 | #print(dataOut.data.shape) | |
|
|
1006 | 1006 | return dataOut |
|
|
1007 | 1007 | |
|
|
1008 | 1008 | """ |
|
|
1009 | 1009 | data dimension = [nChannels, nHeis] |
|
|
1010 | 1010 | """ |
|
|
1011 | 1011 | |
|
|
1012 | 1012 | if profileList != None: |
|
|
1013 | 1013 | |
|
|
1014 | 1014 | if self.isThisProfileInList(dataOut.profileIndex, profileList): |
|
|
1015 | 1015 | |
|
|
1016 | 1016 | self.nProfiles = len(profileList) |
|
|
1017 | 1017 | dataOut.nProfiles = self.nProfiles |
|
|
1018 | 1018 | dataOut.profileIndex = self.profileIndex |
|
|
1019 | 1019 | dataOut.flagNoData = False |
|
|
1020 | 1020 | |
|
|
1021 | 1021 | self.incProfileIndex() |
|
|
1022 | 1022 | return dataOut |
|
|
1023 | 1023 | |
|
|
1024 | 1024 | if profileRangeList != None: |
|
|
1025 | 1025 | |
|
|
1026 | 1026 | minIndex = profileRangeList[0] |
|
|
1027 | 1027 | maxIndex = profileRangeList[1] |
|
|
1028 | 1028 | |
|
|
1029 | 1029 | if self.isThisProfileInRange(dataOut.profileIndex, minIndex, maxIndex): |
|
|
1030 | 1030 | |
|
|
1031 | 1031 | self.nProfiles = maxIndex - minIndex + 1 |
|
|
1032 | 1032 | dataOut.nProfiles = self.nProfiles |
|
|
1033 | 1033 | dataOut.profileIndex = self.profileIndex |
|
|
1034 | 1034 | dataOut.flagNoData = False |
|
|
1035 | 1035 | |
|
|
1036 | 1036 | self.incProfileIndex() |
|
|
1037 | 1037 | return dataOut |
|
|
1038 | 1038 | |
|
|
1039 | 1039 | if rangeList != None: |
|
|
1040 | 1040 | |
|
|
1041 | 1041 | nProfiles = 0 |
|
|
1042 | 1042 | |
|
|
1043 | 1043 | for thisRange in rangeList: |
|
|
1044 | 1044 | minIndex = thisRange[0] |
|
|
1045 | 1045 | maxIndex = thisRange[1] |
|
|
1046 | 1046 | |
|
|
1047 | 1047 | nProfiles += maxIndex - minIndex + 1 |
|
|
1048 | 1048 | |
|
|
1049 | 1049 | for thisRange in rangeList: |
|
|
1050 | 1050 | |
|
|
1051 | 1051 | minIndex = thisRange[0] |
|
|
1052 | 1052 | maxIndex = thisRange[1] |
|
|
1053 | 1053 | |
|
|
1054 | 1054 | if self.isThisProfileInRange(dataOut.profileIndex, minIndex, maxIndex): |
|
|
1055 | 1055 | |
|
|
1056 | 1056 | self.nProfiles = nProfiles |
|
|
1057 | 1057 | dataOut.nProfiles = self.nProfiles |
|
|
1058 | 1058 | dataOut.profileIndex = self.profileIndex |
|
|
1059 | 1059 | dataOut.flagNoData = False |
|
|
1060 | 1060 | |
|
|
1061 | 1061 | self.incProfileIndex() |
|
|
1062 | 1062 | |
|
|
1063 | 1063 | break |
|
|
1064 | 1064 | |
|
|
1065 | 1065 | return dataOut |
|
|
1066 | 1066 | |
|
|
1067 | 1067 | |
|
|
1068 | 1068 | if beam != None: #beam is only for AMISR data |
|
|
1069 | 1069 | if self.isThisProfileInList(dataOut.profileIndex, dataOut.beamRangeDict[beam]): |
|
|
1070 | 1070 | dataOut.flagNoData = False |
|
|
1071 | 1071 | dataOut.profileIndex = self.profileIndex |
|
|
1072 | 1072 | |
|
|
1073 | 1073 | self.incProfileIndex() |
|
|
1074 | 1074 | |
|
|
1075 | 1075 | return dataOut |
|
|
1076 | 1076 | |
|
|
1077 | 1077 | raise ValueError("ProfileSelector needs profileList, profileRangeList or rangeList parameter") |
|
|
1078 | 1078 | |
|
|
1079 | 1079 | |
|
|
1080 | 1080 | class Reshaper(Operation): |
|
|
1081 | 1081 | |
|
|
1082 | 1082 | def __init__(self, **kwargs): |
|
|
1083 | 1083 | |
|
|
1084 | 1084 | Operation.__init__(self, **kwargs) |
|
|
1085 | 1085 | |
|
|
1086 | 1086 | self.__buffer = None |
|
|
1087 | 1087 | self.__nitems = 0 |
|
|
1088 | 1088 | |
|
|
1089 | 1089 | def __appendProfile(self, dataOut, nTxs): |
|
|
1090 | 1090 | |
|
|
1091 | 1091 | if self.__buffer is None: |
|
|
1092 | 1092 | shape = (dataOut.nChannels, int(dataOut.nHeights/nTxs) ) |
|
|
1093 | 1093 | self.__buffer = numpy.empty(shape, dtype = dataOut.data.dtype) |
|
|
1094 | 1094 | |
|
|
1095 | 1095 | ini = dataOut.nHeights * self.__nitems |
|
|
1096 | 1096 | end = ini + dataOut.nHeights |
|
|
1097 | 1097 | |
|
|
1098 | 1098 | self.__buffer[:, ini:end] = dataOut.data |
|
|
1099 | 1099 | |
|
|
1100 | 1100 | self.__nitems += 1 |
|
|
1101 | 1101 | |
|
|
1102 | 1102 | return int(self.__nitems*nTxs) |
|
|
1103 | 1103 | |
|
|
1104 | 1104 | def __getBuffer(self): |
|
|
1105 | 1105 | |
|
|
1106 | 1106 | if self.__nitems == int(1./self.__nTxs): |
|
|
1107 | 1107 | |
|
|
1108 | 1108 | self.__nitems = 0 |
|
|
1109 | 1109 | |
|
|
1110 | 1110 | return self.__buffer.copy() |
|
|
1111 | 1111 | |
|
|
1112 | 1112 | return None |
|
|
1113 | 1113 | |
|
|
1114 | 1114 | def __checkInputs(self, dataOut, shape, nTxs): |
|
|
1115 | 1115 | |
|
|
1116 | 1116 | if shape is None and nTxs is None: |
|
|
1117 | 1117 | raise ValueError("Reshaper: shape of factor should be defined") |
|
|
1118 | 1118 | |
|
|
1119 | 1119 | if nTxs: |
|
|
1120 | 1120 | if nTxs < 0: |
|
|
1121 | 1121 | raise ValueError("nTxs should be greater than 0") |
|
|
1122 | 1122 | |
|
|
1123 | 1123 | if nTxs < 1 and dataOut.nProfiles % (1./nTxs) != 0: |
|
|
1124 | 1124 | raise ValueError("nProfiles= %d is not divisibled by (1./nTxs) = %f" %(dataOut.nProfiles, (1./nTxs))) |
|
|
1125 | 1125 | |
|
|
1126 | 1126 | shape = [dataOut.nChannels, dataOut.nProfiles*nTxs, dataOut.nHeights/nTxs] |
|
|
1127 | 1127 | |
|
|
1128 | 1128 | return shape, nTxs |
|
|
1129 | 1129 | |
|
|
1130 | 1130 | if len(shape) != 2 and len(shape) != 3: |
|
|
1131 | 1131 | raise ValueError("shape dimension should be equal to 2 or 3. shape = (nProfiles, nHeis) or (nChannels, nProfiles, nHeis). Actually shape = (%d, %d, %d)" %(dataOut.nChannels, dataOut.nProfiles, dataOut.nHeights)) |
|
|
1132 | 1132 | |
|
|
1133 | 1133 | if len(shape) == 2: |
|
|
1134 | 1134 | shape_tuple = [dataOut.nChannels] |
|
|
1135 | 1135 | shape_tuple.extend(shape) |
|
|
1136 | 1136 | else: |
|
|
1137 | 1137 | shape_tuple = list(shape) |
|
|
1138 | 1138 | |
|
|
1139 | 1139 | nTxs = 1.0*shape_tuple[1]/dataOut.nProfiles |
|
|
1140 | 1140 | |
|
|
1141 | 1141 | return shape_tuple, nTxs |
|
|
1142 | 1142 | |
|
|
1143 | 1143 | def run(self, dataOut, shape=None, nTxs=None): |
|
|
1144 | 1144 | |
|
|
1145 | 1145 | shape_tuple, self.__nTxs = self.__checkInputs(dataOut, shape, nTxs) |
|
|
1146 | 1146 | |
|
|
1147 | 1147 | dataOut.flagNoData = True |
|
|
1148 | 1148 | profileIndex = None |
|
|
1149 | 1149 | |
|
|
1150 | 1150 | if dataOut.flagDataAsBlock: |
|
|
1151 | 1151 | |
|
|
1152 | 1152 | dataOut.data = numpy.reshape(dataOut.data, shape_tuple) |
|
|
1153 | 1153 | dataOut.flagNoData = False |
|
|
1154 | 1154 | |
|
|
1155 | 1155 | profileIndex = int(dataOut.nProfiles*self.__nTxs) - 1 |
|
|
1156 | 1156 | |
|
|
1157 | 1157 | else: |
|
|
1158 | 1158 | |
|
|
1159 | 1159 | if self.__nTxs < 1: |
|
|
1160 | 1160 | |
|
|
1161 | 1161 | self.__appendProfile(dataOut, self.__nTxs) |
|
|
1162 | 1162 | new_data = self.__getBuffer() |
|
|
1163 | 1163 | |
|
|
1164 | 1164 | if new_data is not None: |
|
|
1165 | 1165 | dataOut.data = new_data |
|
|
1166 | 1166 | dataOut.flagNoData = False |
|
|
1167 | 1167 | |
|
|
1168 | 1168 | profileIndex = dataOut.profileIndex*nTxs |
|
|
1169 | 1169 | |
|
|
1170 | 1170 | else: |
|
|
1171 | 1171 | raise ValueError("nTxs should be greater than 0 and lower than 1, or use VoltageReader(..., getblock=True)") |
|
|
1172 | 1172 | |
|
|
1173 | 1173 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] |
|
|
1174 | 1174 | |
|
|
1175 | 1175 | dataOut.heightList = numpy.arange(dataOut.nHeights/self.__nTxs) * deltaHeight + dataOut.heightList[0] |
|
|
1176 | 1176 | |
|
|
1177 | 1177 | dataOut.nProfiles = int(dataOut.nProfiles*self.__nTxs) |
|
|
1178 | 1178 | |
|
|
1179 | 1179 | dataOut.profileIndex = profileIndex |
|
|
1180 | 1180 | |
|
|
1181 | 1181 | dataOut.ippSeconds /= self.__nTxs |
|
|
1182 | 1182 | |
|
|
1183 | 1183 | return dataOut |
|
|
1184 | 1184 | |
|
|
1185 | 1185 | class SplitProfiles(Operation): |
|
|
1186 | 1186 | |
|
|
1187 | 1187 | def __init__(self, **kwargs): |
|
|
1188 | 1188 | |
|
|
1189 | 1189 | Operation.__init__(self, **kwargs) |
|
|
1190 | 1190 | |
|
|
1191 | 1191 | def run(self, dataOut, n): |
|
|
1192 | 1192 | |
|
|
1193 | 1193 | dataOut.flagNoData = True |
|
|
1194 | 1194 | profileIndex = None |
|
|
1195 | 1195 | |
|
|
1196 | 1196 | if dataOut.flagDataAsBlock: |
|
|
1197 | 1197 | |
|
|
1198 | 1198 | #nchannels, nprofiles, nsamples |
|
|
1199 | 1199 | shape = dataOut.data.shape |
|
|
1200 | 1200 | |
|
|
1201 | 1201 | if shape[2] % n != 0: |
|
|
1202 | 1202 | raise ValueError("Could not split the data, n=%d has to be multiple of %d" %(n, shape[2])) |
|
|
1203 | 1203 | |
|
|
1204 | 1204 | new_shape = shape[0], shape[1]*n, int(shape[2]/n) |
|
|
1205 | 1205 | |
|
|
1206 | 1206 | dataOut.data = numpy.reshape(dataOut.data, new_shape) |
|
|
1207 | 1207 | dataOut.flagNoData = False |
|
|
1208 | 1208 | |
|
|
1209 | 1209 | profileIndex = int(dataOut.nProfiles/n) - 1 |
|
|
1210 | 1210 | |
|
|
1211 | 1211 | else: |
|
|
1212 | 1212 | |
|
|
1213 | 1213 | raise ValueError("Could not split the data when is read Profile by Profile. Use VoltageReader(..., getblock=True)") |
|
|
1214 | 1214 | |
|
|
1215 | 1215 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] |
|
|
1216 | 1216 | |
|
|
1217 | 1217 | dataOut.heightList = numpy.arange(dataOut.nHeights/n) * deltaHeight + dataOut.heightList[0] |
|
|
1218 | 1218 | |
|
|
1219 | 1219 | dataOut.nProfiles = int(dataOut.nProfiles*n) |
|
|
1220 | 1220 | |
|
|
1221 | 1221 | dataOut.profileIndex = profileIndex |
|
|
1222 | 1222 | |
|
|
1223 | 1223 | dataOut.ippSeconds /= n |
|
|
1224 | 1224 | |
|
|
1225 | 1225 | return dataOut |
|
|
1226 | 1226 | |
|
|
1227 | 1227 | class CombineProfiles(Operation): |
|
|
1228 | 1228 | def __init__(self, **kwargs): |
|
|
1229 | 1229 | |
|
|
1230 | 1230 | Operation.__init__(self, **kwargs) |
|
|
1231 | 1231 | |
|
|
1232 | 1232 | self.__remData = None |
|
|
1233 | 1233 | self.__profileIndex = 0 |
|
|
1234 | 1234 | |
|
|
1235 | 1235 | def run(self, dataOut, n): |
|
|
1236 | 1236 | |
|
|
1237 | 1237 | dataOut.flagNoData = True |
|
|
1238 | 1238 | profileIndex = None |
|
|
1239 | 1239 | |
|
|
1240 | 1240 | if dataOut.flagDataAsBlock: |
|
|
1241 | 1241 | |
|
|
1242 | 1242 | #nchannels, nprofiles, nsamples |
|
|
1243 | 1243 | shape = dataOut.data.shape |
|
|
1244 | 1244 | new_shape = shape[0], shape[1]/n, shape[2]*n |
|
|
1245 | 1245 | |
|
|
1246 | 1246 | if shape[1] % n != 0: |
|
|
1247 | 1247 | raise ValueError("Could not split the data, n=%d has to be multiple of %d" %(n, shape[1])) |
|
|
1248 | 1248 | |
|
|
1249 | 1249 | dataOut.data = numpy.reshape(dataOut.data, new_shape) |
|
|
1250 | 1250 | dataOut.flagNoData = False |
|
|
1251 | 1251 | |
|
|
1252 | 1252 | profileIndex = int(dataOut.nProfiles*n) - 1 |
|
|
1253 | 1253 | |
|
|
1254 | 1254 | else: |
|
|
1255 | 1255 | |
|
|
1256 | 1256 | #nchannels, nsamples |
|
|
1257 | 1257 | if self.__remData is None: |
|
|
1258 | 1258 | newData = dataOut.data |
|
|
1259 | 1259 | else: |
|
|
1260 | 1260 | newData = numpy.concatenate((self.__remData, dataOut.data), axis=1) |
|
|
1261 | 1261 | |
|
|
1262 | 1262 | self.__profileIndex += 1 |
|
|
1263 | 1263 | |
|
|
1264 | 1264 | if self.__profileIndex < n: |
|
|
1265 | 1265 | self.__remData = newData |
|
|
1266 | 1266 | #continue |
|
|
1267 | 1267 | return |
|
|
1268 | 1268 | |
|
|
1269 | 1269 | self.__profileIndex = 0 |
|
|
1270 | 1270 | self.__remData = None |
|
|
1271 | 1271 | |
|
|
1272 | 1272 | dataOut.data = newData |
|
|
1273 | 1273 | dataOut.flagNoData = False |
|
|
1274 | 1274 | |
|
|
1275 | 1275 | profileIndex = dataOut.profileIndex/n |
|
|
1276 | 1276 | |
|
|
1277 | 1277 | |
|
|
1278 | 1278 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] |
|
|
1279 | 1279 | |
|
|
1280 | 1280 | dataOut.heightList = numpy.arange(dataOut.nHeights*n) * deltaHeight + dataOut.heightList[0] |
|
|
1281 | 1281 | |
|
|
1282 | 1282 | dataOut.nProfiles = int(dataOut.nProfiles/n) |
|
|
1283 | 1283 | |
|
|
1284 | 1284 | dataOut.profileIndex = profileIndex |
|
|
1285 | 1285 | |
|
|
1286 | 1286 | dataOut.ippSeconds *= n |
|
|
1287 | 1287 | |
|
|
1288 | 1288 | return dataOut |
|
|
1289 | 1289 | |
|
|
1290 | 1290 | class PulsePair(Operation): |
|
|
1291 | 1291 | ''' |
|
|
1292 | 1292 | Function PulsePair(Signal Power, Velocity) |
|
|
1293 | 1293 | The real component of Lag[0] provides Intensity Information |
|
|
1294 | 1294 | The imag component of Lag[1] Phase provides Velocity Information |
|
|
1295 | 1295 | |
|
|
1296 | 1296 | Configuration Parameters: |
|
|
1297 | 1297 | nPRF = Number of Several PRF |
|
|
1298 | 1298 | theta = Degree Azimuth angel Boundaries |
|
|
1299 | 1299 | |
|
|
1300 | 1300 | Input: |
|
|
1301 | 1301 | self.dataOut |
|
|
1302 | 1302 | lag[N] |
|
|
1303 | 1303 | Affected: |
|
|
1304 | 1304 | self.dataOut.spc |
|
|
1305 | 1305 | ''' |
|
|
1306 | 1306 | isConfig = False |
|
|
1307 | 1307 | __profIndex = 0 |
|
|
1308 | 1308 | __initime = None |
|
|
1309 | 1309 | __lastdatatime = None |
|
|
1310 | 1310 | __buffer = None |
|
|
1311 | 1311 | noise = None |
|
|
1312 | 1312 | __dataReady = False |
|
|
1313 | 1313 | n = None |
|
|
1314 | 1314 | __nch = 0 |
|
|
1315 | 1315 | __nHeis = 0 |
|
|
1316 | 1316 | removeDC = False |
|
|
1317 | 1317 | ipp = None |
|
|
1318 | 1318 | lambda_ = 0 |
|
|
1319 | 1319 | |
|
|
1320 | 1320 | def __init__(self,**kwargs): |
|
|
1321 | 1321 | Operation.__init__(self,**kwargs) |
|
|
1322 | 1322 | |
|
|
1323 | 1323 | def setup(self, dataOut, n = None, removeDC=False): |
|
|
1324 | 1324 | ''' |
|
|
1325 | 1325 | n= Numero de PRF's de entrada |
|
|
1326 | 1326 | ''' |
|
|
1327 | 1327 | self.__initime = None |
|
|
1328 | 1328 | ####print("[INICIO]-setup del METODO PULSE PAIR") |
|
|
1329 | 1329 | self.__lastdatatime = 0 |
|
|
1330 | 1330 | self.__dataReady = False |
|
|
1331 | 1331 | self.__buffer = 0 |
|
|
1332 | 1332 | self.__profIndex = 0 |
|
|
1333 | 1333 | self.noise = None |
|
|
1334 | 1334 | self.__nch = dataOut.nChannels |
|
|
1335 | 1335 | self.__nHeis = dataOut.nHeights |
|
|
1336 | 1336 | self.removeDC = removeDC |
|
|
1337 | 1337 | self.lambda_ = 3.0e8/(9345.0e6) |
|
|
1338 | 1338 | self.ippSec = dataOut.ippSeconds |
|
|
1339 | 1339 | self.nCohInt = dataOut.nCohInt |
|
|
1340 | 1340 | ####print("IPPseconds",dataOut.ippSeconds) |
|
|
1341 | 1341 | ####print("ELVALOR DE n es:", n) |
|
|
1342 | 1342 | if n == None: |
|
|
1343 | 1343 | raise ValueError("n should be specified.") |
|
|
1344 | 1344 | |
|
|
1345 | 1345 | if n != None: |
|
|
1346 | 1346 | if n<2: |
|
|
1347 | 1347 | raise ValueError("n should be greater than 2") |
|
|
1348 | 1348 | |
|
|
1349 | 1349 | self.n = n |
|
|
1350 | 1350 | self.__nProf = n |
|
|
1351 | 1351 | |
|
|
1352 | 1352 | self.__buffer = numpy.zeros((dataOut.nChannels, |
|
|
1353 | 1353 | n, |
|
|
1354 | 1354 | dataOut.nHeights), |
|
|
1355 | 1355 | dtype='complex') |
|
|
1356 | 1356 | |
|
|
1357 | 1357 | def putData(self,data): |
|
|
1358 | 1358 | ''' |
|
|
1359 | 1359 | Add a profile to he __buffer and increase in one the __profiel Index |
|
|
1360 | 1360 | ''' |
|
|
1361 | 1361 | self.__buffer[:,self.__profIndex,:]= data |
|
|
1362 | 1362 | self.__profIndex += 1 |
|
|
1363 | 1363 | return |
|
|
1364 | 1364 | |
|
|
1365 | 1365 | def pushData(self,dataOut): |
|
|
1366 | 1366 | ''' |
|
|
1367 | 1367 | Return the PULSEPAIR and the profiles used in the operation |
|
|
1368 | 1368 | Affected : self.__profileIndex |
|
|
1369 | 1369 | ''' |
|
|
1370 | 1370 | #----------------- Remove DC----------------------------------- |
|
|
1371 | 1371 | if self.removeDC==True: |
|
|
1372 | 1372 | mean = numpy.mean(self.__buffer,1) |
|
|
1373 | 1373 | tmp = mean.reshape(self.__nch,1,self.__nHeis) |
|
|
1374 | 1374 | dc= numpy.tile(tmp,[1,self.__nProf,1]) |
|
|
1375 | 1375 | self.__buffer = self.__buffer - dc |
|
|
1376 | 1376 | #------------------Calculo de Potencia ------------------------ |
|
|
1377 | 1377 | pair0 = self.__buffer*numpy.conj(self.__buffer) |
|
|
1378 | 1378 | pair0 = pair0.real |
|
|
1379 | 1379 | lag_0 = numpy.sum(pair0,1) |
|
|
1380 | 1380 | #-----------------Calculo de Cscp------------------------------ New |
|
|
1381 | 1381 | cspc_pair01 = self.__buffer[0]*self.__buffer[1] |
|
|
1382 | 1382 | #------------------Calculo de Ruido x canal-------------------- |
|
|
1383 | 1383 | self.noise = numpy.zeros(self.__nch) |
|
|
1384 | 1384 | for i in range(self.__nch): |
|
|
1385 | 1385 | daux = numpy.sort(pair0[i,:,:],axis= None) |
|
|
1386 | 1386 | self.noise[i]=hildebrand_sekhon( daux ,self.nCohInt) |
|
|
1387 | 1387 | |
|
|
1388 | 1388 | self.noise = self.noise.reshape(self.__nch,1) |
|
|
1389 | 1389 | self.noise = numpy.tile(self.noise,[1,self.__nHeis]) |
|
|
1390 | 1390 | noise_buffer = self.noise.reshape(self.__nch,1,self.__nHeis) |
|
|
1391 | 1391 | noise_buffer = numpy.tile(noise_buffer,[1,self.__nProf,1]) |
|
|
1392 | 1392 | #------------------ Potencia recibida= P , Potencia senal = S , Ruido= N-- |
|
|
1393 | 1393 | #------------------ P= S+N ,P=lag_0/N --------------------------------- |
|
|
1394 | 1394 | #-------------------- Power -------------------------------------------------- |
|
|
1395 | 1395 | data_power = lag_0/(self.n*self.nCohInt) |
|
|
1396 | 1396 | #--------------------CCF------------------------------------------------------ |
|
|
1397 | 1397 | data_ccf =numpy.sum(cspc_pair01,axis=0)/(self.n*self.nCohInt) |
|
|
1398 | 1398 | #------------------ Senal -------------------------------------------------- |
|
|
1399 | 1399 | data_intensity = pair0 - noise_buffer |
|
|
1400 | 1400 | data_intensity = numpy.sum(data_intensity,axis=1)*(self.n*self.nCohInt)#*self.nCohInt) |
|
|
1401 | 1401 | #data_intensity = (lag_0-self.noise*self.n)*(self.n*self.nCohInt) |
|
|
1402 | 1402 | for i in range(self.__nch): |
|
|
1403 | 1403 | for j in range(self.__nHeis): |
|
|
1404 | 1404 | if data_intensity[i][j] < 0: |
|
|
1405 | 1405 | data_intensity[i][j] = numpy.min(numpy.absolute(data_intensity[i][j])) |
|
|
1406 | 1406 | |
|
|
1407 | 1407 | #----------------- Calculo de Frecuencia y Velocidad doppler-------- |
|
|
1408 | 1408 | pair1 = self.__buffer[:,:-1,:]*numpy.conjugate(self.__buffer[:,1:,:]) |
|
|
1409 | 1409 | lag_1 = numpy.sum(pair1,1) |
|
|
1410 | 1410 | data_freq = (-1/(2.0*math.pi*self.ippSec*self.nCohInt))*numpy.angle(lag_1) |
|
|
1411 | 1411 | data_velocity = (self.lambda_/2.0)*data_freq |
|
|
1412 | 1412 | |
|
|
1413 | 1413 | #---------------- Potencia promedio estimada de la Senal----------- |
|
|
1414 | 1414 | lag_0 = lag_0/self.n |
|
|
1415 | 1415 | S = lag_0-self.noise |
|
|
1416 | 1416 | |
|
|
1417 | 1417 | #---------------- Frecuencia Doppler promedio --------------------- |
|
|
1418 | 1418 | lag_1 = lag_1/(self.n-1) |
|
|
1419 | 1419 | R1 = numpy.abs(lag_1) |
|
|
1420 | 1420 | |
|
|
1421 | 1421 | #---------------- Calculo del SNR---------------------------------- |
|
|
1422 | 1422 | data_snrPP = S/self.noise |
|
|
1423 | 1423 | for i in range(self.__nch): |
|
|
1424 | 1424 | for j in range(self.__nHeis): |
|
|
1425 | 1425 | if data_snrPP[i][j] < 1.e-20: |
|
|
1426 | 1426 | data_snrPP[i][j] = 1.e-20 |
|
|
1427 | 1427 | |
|
|
1428 | 1428 | #----------------- Calculo del ancho espectral ---------------------- |
|
|
1429 | 1429 | L = S/R1 |
|
|
1430 | 1430 | L = numpy.where(L<0,1,L) |
|
|
1431 | 1431 | L = numpy.log(L) |
|
|
1432 | 1432 | tmp = numpy.sqrt(numpy.absolute(L)) |
|
|
1433 | 1433 | data_specwidth = (self.lambda_/(2*math.sqrt(2)*math.pi*self.ippSec*self.nCohInt))*tmp*numpy.sign(L) |
|
|
1434 | 1434 | n = self.__profIndex |
|
|
1435 | 1435 | |
|
|
1436 | 1436 | self.__buffer = numpy.zeros((self.__nch, self.__nProf,self.__nHeis), dtype='complex') |
|
|
1437 | 1437 | self.__profIndex = 0 |
|
|
1438 | 1438 | return data_power,data_intensity,data_velocity,data_snrPP,data_specwidth,data_ccf,n |
|
|
1439 | 1439 | |
|
|
1440 | 1440 | |
|
|
1441 | 1441 | def pulsePairbyProfiles(self,dataOut): |
|
|
1442 | 1442 | |
|
|
1443 | 1443 | self.__dataReady = False |
|
|
1444 | 1444 | data_power = None |
|
|
1445 | 1445 | data_intensity = None |
|
|
1446 | 1446 | data_velocity = None |
|
|
1447 | 1447 | data_specwidth = None |
|
|
1448 | 1448 | data_snrPP = None |
|
|
1449 | 1449 | data_ccf = None |
|
|
1450 | 1450 | self.putData(data=dataOut.data) |
|
|
1451 | 1451 | if self.__profIndex == self.n: |
|
|
1452 | 1452 | data_power,data_intensity, data_velocity,data_snrPP,data_specwidth,data_ccf, n = self.pushData(dataOut=dataOut) |
|
|
1453 | 1453 | self.__dataReady = True |
|
|
1454 | 1454 | |
|
|
1455 | 1455 | return data_power, data_intensity, data_velocity, data_snrPP,data_specwidth,data_ccf |
|
|
1456 | 1456 | |
|
|
1457 | 1457 | |
|
|
1458 | 1458 | def pulsePairOp(self, dataOut, datatime= None): |
|
|
1459 | 1459 | |
|
|
1460 | 1460 | if self.__initime == None: |
|
|
1461 | 1461 | self.__initime = datatime |
|
|
1462 | 1462 | data_power, data_intensity, data_velocity, data_snrPP,data_specwidth,data_ccf = self.pulsePairbyProfiles(dataOut) |
|
|
1463 | 1463 | self.__lastdatatime = datatime |
|
|
1464 | 1464 | |
|
|
1465 | 1465 | if data_power is None: |
|
|
1466 | 1466 | return None, None, None,None,None,None,None |
|
|
1467 | 1467 | |
|
|
1468 | 1468 | avgdatatime = self.__initime |
|
|
1469 | 1469 | deltatime = datatime - self.__lastdatatime |
|
|
1470 | 1470 | self.__initime = datatime |
|
|
1471 | 1471 | |
|
|
1472 | 1472 | return data_power, data_intensity, data_velocity, data_snrPP,data_specwidth,data_ccf, avgdatatime |
|
|
1473 | 1473 | |
|
|
1474 | 1474 | def run(self, dataOut,n = None,removeDC= False, overlapping= False,**kwargs): |
|
|
1475 | 1475 | #print("hey") |
|
|
1476 | 1476 | #print(dataOut.data.shape) |
|
|
1477 | 1477 | #exit(1) |
|
|
1478 | 1478 | #print(self.__profIndex) |
|
|
1479 | 1479 | if not self.isConfig: |
|
|
1480 | 1480 | self.setup(dataOut = dataOut, n = n , removeDC=removeDC , **kwargs) |
|
|
1481 | 1481 | self.isConfig = True |
|
|
1482 | 1482 | data_power, data_intensity, data_velocity,data_snrPP,data_specwidth,data_ccf, avgdatatime = self.pulsePairOp(dataOut, dataOut.utctime) |
|
|
1483 | 1483 | dataOut.flagNoData = True |
|
|
1484 | 1484 | |
|
|
1485 | 1485 | if self.__dataReady: |
|
|
1486 | 1486 | ###print("READY ----------------------------------") |
|
|
1487 | 1487 | dataOut.nCohInt *= self.n |
|
|
1488 | 1488 | dataOut.dataPP_POW = data_intensity # S |
|
|
1489 | 1489 | dataOut.dataPP_POWER = data_power # P valor que corresponde a POTENCIA MOMENTO |
|
|
1490 | 1490 | dataOut.dataPP_DOP = data_velocity |
|
|
1491 | 1491 | dataOut.dataPP_SNR = data_snrPP |
|
|
1492 | 1492 | dataOut.dataPP_WIDTH = data_specwidth |
|
|
1493 | 1493 | dataOut.dataPP_CCF = data_ccf |
|
|
1494 | 1494 | dataOut.PRFbyAngle = self.n #numero de PRF*cada angulo rotado que equivale a un tiempo. |
|
|
1495 | 1495 | dataOut.nProfiles = int(dataOut.nProfiles/n) |
|
|
1496 | 1496 | dataOut.utctime = avgdatatime |
|
|
1497 | 1497 | dataOut.flagNoData = False |
|
|
1498 | 1498 | return dataOut |
|
|
1499 | 1499 | |
|
|
1500 | 1500 | class PulsePair_vRF(Operation): |
|
|
1501 | 1501 | ''' |
|
|
1502 | 1502 | Function PulsePair(Signal Power, Velocity) |
|
|
1503 | 1503 | The real component of Lag[0] provides Intensity Information |
|
|
1504 | 1504 | The imag component of Lag[1] Phase provides Velocity Information |
|
|
1505 | 1505 | |
|
|
1506 | 1506 | Configuration Parameters: |
|
|
1507 | 1507 | nPRF = Number of Several PRF |
|
|
1508 | 1508 | theta = Degree Azimuth angel Boundaries |
|
|
1509 | 1509 | |
|
|
1510 | 1510 | Input: |
|
|
1511 | 1511 | self.dataOut |
|
|
1512 | 1512 | lag[N] |
|
|
1513 | 1513 | Affected: |
|
|
1514 | 1514 | self.dataOut.spc |
|
|
1515 | 1515 | ''' |
|
|
1516 | 1516 | isConfig = False |
|
|
1517 | 1517 | __profIndex = 0 |
|
|
1518 | 1518 | __initime = None |
|
|
1519 | 1519 | __lastdatatime = None |
|
|
1520 | 1520 | __buffer = None |
|
|
1521 | 1521 | noise = None |
|
|
1522 | 1522 | __dataReady = False |
|
|
1523 | 1523 | n = None |
|
|
1524 | 1524 | __nch = 0 |
|
|
1525 | 1525 | __nHeis = 0 |
|
|
1526 | 1526 | removeDC = False |
|
|
1527 | 1527 | ipp = None |
|
|
1528 | 1528 | lambda_ = 0 |
|
|
1529 | 1529 | |
|
|
1530 | 1530 | def __init__(self,**kwargs): |
|
|
1531 | 1531 | Operation.__init__(self,**kwargs) |
|
|
1532 | 1532 | |
|
|
1533 | 1533 | def setup(self, dataOut, n = None, removeDC=False): |
|
|
1534 | 1534 | ''' |
|
|
1535 | 1535 | n= Numero de PRF's de entrada |
|
|
1536 | 1536 | ''' |
|
|
1537 | 1537 | self.__initime = None |
|
|
1538 | 1538 | ####print("[INICIO]-setup del METODO PULSE PAIR") |
|
|
1539 | 1539 | self.__lastdatatime = 0 |
|
|
1540 | 1540 | self.__dataReady = False |
|
|
1541 | 1541 | self.__buffer = 0 |
|
|
1542 | 1542 | self.__profIndex = 0 |
|
|
1543 | 1543 | self.noise = None |
|
|
1544 | 1544 | self.__nch = dataOut.nChannels |
|
|
1545 | 1545 | self.__nHeis = dataOut.nHeights |
|
|
1546 | 1546 | self.removeDC = removeDC |
|
|
1547 | 1547 | self.lambda_ = 3.0e8/(9345.0e6) |
|
|
1548 | 1548 | self.ippSec = dataOut.ippSeconds |
|
|
1549 | 1549 | self.nCohInt = dataOut.nCohInt |
|
|
1550 | 1550 | ####print("IPPseconds",dataOut.ippSeconds) |
|
|
1551 | 1551 | ####print("ELVALOR DE n es:", n) |
|
|
1552 | 1552 | if n == None: |
|
|
1553 | 1553 | raise ValueError("n should be specified.") |
|
|
1554 | 1554 | |
|
|
1555 | 1555 | if n != None: |
|
|
1556 | 1556 | if n<2: |
|
|
1557 | 1557 | raise ValueError("n should be greater than 2") |
|
|
1558 | 1558 | |
|
|
1559 | 1559 | self.n = n |
|
|
1560 | 1560 | self.__nProf = n |
|
|
1561 | 1561 | |
|
|
1562 | 1562 | self.__buffer = numpy.zeros((dataOut.nChannels, |
|
|
1563 | 1563 | n, |
|
|
1564 | 1564 | dataOut.nHeights), |
|
|
1565 | 1565 | dtype='complex') |
|
|
1566 | 1566 | |
|
|
1567 | 1567 | def putData(self,data): |
|
|
1568 | 1568 | ''' |
|
|
1569 | 1569 | Add a profile to he __buffer and increase in one the __profiel Index |
|
|
1570 | 1570 | ''' |
|
|
1571 | 1571 | self.__buffer[:,self.__profIndex,:]= data |
|
|
1572 | 1572 | self.__profIndex += 1 |
|
|
1573 | 1573 | return |
|
|
1574 | 1574 | |
|
|
1575 | 1575 | def putDataByBlock(self,data,n): |
|
|
1576 | 1576 | ''' |
|
|
1577 | 1577 | Add a profile to he __buffer and increase in one the __profiel Index |
|
|
1578 | 1578 | ''' |
|
|
1579 | 1579 | self.__buffer[:]= data |
|
|
1580 | 1580 | self.__profIndex = n |
|
|
1581 | 1581 | return |
|
|
1582 | 1582 | |
|
|
1583 | 1583 | def pushData(self,dataOut): |
|
|
1584 | 1584 | ''' |
|
|
1585 | 1585 | Return the PULSEPAIR and the profiles used in the operation |
|
|
1586 | 1586 | Affected : self.__profileIndex |
|
|
1587 | 1587 | ''' |
|
|
1588 | 1588 | #----------------- Remove DC----------------------------------- |
|
|
1589 | 1589 | if self.removeDC==True: |
|
|
1590 | 1590 | mean = numpy.mean(self.__buffer,1) |
|
|
1591 | 1591 | tmp = mean.reshape(self.__nch,1,self.__nHeis) |
|
|
1592 | 1592 | dc= numpy.tile(tmp,[1,self.__nProf,1]) |
|
|
1593 | 1593 | self.__buffer = self.__buffer - dc |
|
|
1594 | 1594 | #------------------Calculo de Potencia ------------------------ |
|
|
1595 | 1595 | pair0 = self.__buffer*numpy.conj(self.__buffer) |
|
|
1596 | 1596 | pair0 = pair0.real |
|
|
1597 | 1597 | lag_0 = numpy.sum(pair0,1) |
|
|
1598 | 1598 | #-----------------Calculo de Cscp------------------------------ New |
|
|
1599 | 1599 | cspc_pair01 = self.__buffer[0]*self.__buffer[1] |
|
|
1600 | 1600 | #------------------Calculo de Ruido x canal-------------------- |
|
|
1601 | 1601 | self.noise = numpy.zeros(self.__nch) |
|
|
1602 | 1602 | for i in range(self.__nch): |
|
|
1603 | 1603 | daux = numpy.sort(pair0[i,:,:],axis= None) |
|
|
1604 | 1604 | self.noise[i]=hildebrand_sekhon( daux ,self.nCohInt) |
|
|
1605 | 1605 | |
|
|
1606 | 1606 | self.noise = self.noise.reshape(self.__nch,1) |
|
|
1607 | 1607 | self.noise = numpy.tile(self.noise,[1,self.__nHeis]) |
|
|
1608 | 1608 | noise_buffer = self.noise.reshape(self.__nch,1,self.__nHeis) |
|
|
1609 | 1609 | noise_buffer = numpy.tile(noise_buffer,[1,self.__nProf,1]) |
|
|
1610 | 1610 | #------------------ Potencia recibida= P , Potencia senal = S , Ruido= N-- |
|
|
1611 | 1611 | #------------------ P= S+N ,P=lag_0/N --------------------------------- |
|
|
1612 | 1612 | #-------------------- Power -------------------------------------------------- |
|
|
1613 | 1613 | data_power = lag_0/(self.n*self.nCohInt) |
|
|
1614 | 1614 | #--------------------CCF------------------------------------------------------ |
|
|
1615 | 1615 | data_ccf =numpy.sum(cspc_pair01,axis=0)/(self.n*self.nCohInt) |
|
|
1616 | 1616 | #------------------ Senal -------------------------------------------------- |
|
|
1617 | 1617 | data_intensity = pair0 - noise_buffer |
|
|
1618 | 1618 | data_intensity = numpy.sum(data_intensity,axis=1)*(self.n*self.nCohInt)#*self.nCohInt) |
|
|
1619 | 1619 | #data_intensity = (lag_0-self.noise*self.n)*(self.n*self.nCohInt) |
|
|
1620 | 1620 | for i in range(self.__nch): |
|
|
1621 | 1621 | for j in range(self.__nHeis): |
|
|
1622 | 1622 | if data_intensity[i][j] < 0: |
|
|
1623 | 1623 | data_intensity[i][j] = numpy.min(numpy.absolute(data_intensity[i][j])) |
|
|
1624 | 1624 | |
|
|
1625 | 1625 | #----------------- Calculo de Frecuencia y Velocidad doppler-------- |
|
|
1626 | 1626 | pair1 = self.__buffer[:,:-1,:]*numpy.conjugate(self.__buffer[:,1:,:]) |
|
|
1627 | 1627 | lag_1 = numpy.sum(pair1,1) |
|
|
1628 | 1628 | data_freq = (-1/(2.0*math.pi*self.ippSec*self.nCohInt))*numpy.angle(lag_1) |
|
|
1629 | 1629 | data_velocity = (self.lambda_/2.0)*data_freq |
|
|
1630 | 1630 | |
|
|
1631 | 1631 | #---------------- Potencia promedio estimada de la Senal----------- |
|
|
1632 | 1632 | lag_0 = lag_0/self.n |
|
|
1633 | 1633 | S = lag_0-self.noise |
|
|
1634 | 1634 | |
|
|
1635 | 1635 | #---------------- Frecuencia Doppler promedio --------------------- |
|
|
1636 | 1636 | lag_1 = lag_1/(self.n-1) |
|
|
1637 | 1637 | R1 = numpy.abs(lag_1) |
|
|
1638 | 1638 | |
|
|
1639 | 1639 | #---------------- Calculo del SNR---------------------------------- |
|
|
1640 | 1640 | data_snrPP = S/self.noise |
|
|
1641 | 1641 | for i in range(self.__nch): |
|
|
1642 | 1642 | for j in range(self.__nHeis): |
|
|
1643 | 1643 | if data_snrPP[i][j] < 1.e-20: |
|
|
1644 | 1644 | data_snrPP[i][j] = 1.e-20 |
|
|
1645 | 1645 | |
|
|
1646 | 1646 | #----------------- Calculo del ancho espectral ---------------------- |
|
|
1647 | 1647 | L = S/R1 |
|
|
1648 | 1648 | L = numpy.where(L<0,1,L) |
|
|
1649 | 1649 | L = numpy.log(L) |
|
|
1650 | 1650 | tmp = numpy.sqrt(numpy.absolute(L)) |
|
|
1651 | 1651 | data_specwidth = (self.lambda_/(2*math.sqrt(2)*math.pi*self.ippSec*self.nCohInt))*tmp*numpy.sign(L) |
|
|
1652 | 1652 | n = self.__profIndex |
|
|
1653 | 1653 | |
|
|
1654 | 1654 | self.__buffer = numpy.zeros((self.__nch, self.__nProf,self.__nHeis), dtype='complex') |
|
|
1655 | 1655 | self.__profIndex = 0 |
|
|
1656 | 1656 | return data_power,data_intensity,data_velocity,data_snrPP,data_specwidth,data_ccf,n |
|
|
1657 | 1657 | |
|
|
1658 | 1658 | |
|
|
1659 | 1659 | def pulsePairbyProfiles(self,dataOut,n): |
|
|
1660 | 1660 | |
|
|
1661 | 1661 | self.__dataReady = False |
|
|
1662 | 1662 | data_power = None |
|
|
1663 | 1663 | data_intensity = None |
|
|
1664 | 1664 | data_velocity = None |
|
|
1665 | 1665 | data_specwidth = None |
|
|
1666 | 1666 | data_snrPP = None |
|
|
1667 | 1667 | data_ccf = None |
|
|
1668 | 1668 | |
|
|
1669 | 1669 | if dataOut.flagDataAsBlock: |
|
|
1670 | 1670 | self.putDataByBlock(data=dataOut.data,n=n) |
|
|
1671 | 1671 | else: |
|
|
1672 | 1672 | self.putData(data=dataOut.data) |
|
|
1673 | 1673 | if self.__profIndex == self.n: |
|
|
1674 | 1674 | data_power,data_intensity, data_velocity,data_snrPP,data_specwidth,data_ccf, n = self.pushData(dataOut=dataOut) |
|
|
1675 | 1675 | self.__dataReady = True |
|
|
1676 | 1676 | |
|
|
1677 | 1677 | return data_power, data_intensity, data_velocity, data_snrPP,data_specwidth,data_ccf |
|
|
1678 | 1678 | |
|
|
1679 | 1679 | |
|
|
1680 | 1680 | def pulsePairOp(self, dataOut, n, datatime= None): |
|
|
1681 | 1681 | |
|
|
1682 | 1682 | if self.__initime == None: |
|
|
1683 | 1683 | self.__initime = datatime |
|
|
1684 | 1684 | data_power, data_intensity, data_velocity, data_snrPP,data_specwidth,data_ccf = self.pulsePairbyProfiles(dataOut,n) |
|
|
1685 | 1685 | self.__lastdatatime = datatime |
|
|
1686 | 1686 | |
|
|
1687 | 1687 | if data_power is None: |
|
|
1688 | 1688 | return None, None, None,None,None,None,None |
|
|
1689 | 1689 | |
|
|
1690 | 1690 | avgdatatime = self.__initime |
|
|
1691 | 1691 | deltatime = datatime - self.__lastdatatime |
|
|
1692 | 1692 | self.__initime = datatime |
|
|
1693 | 1693 | |
|
|
1694 | 1694 | return data_power, data_intensity, data_velocity, data_snrPP,data_specwidth,data_ccf, avgdatatime |
|
|
1695 | 1695 | |
|
|
1696 | 1696 | def run(self, dataOut,n = None,removeDC= False, overlapping= False,**kwargs): |
|
|
1697 | #print("hey") | |
|
|
1698 | #print(dataOut.data.shape) | |
|
|
1699 | #exit(1) | |
|
|
1697 | ||
|
|
1700 | 1698 | if dataOut.flagDataAsBlock: |
|
|
1701 |
n = dataOut.nProfile |
|
|
|
1702 | #print(self.__profIndex) | |
|
|
1699 | n = dataOut.nProfiles | |
|
|
1700 | ||
|
|
1703 | 1701 | if not self.isConfig: |
|
|
1704 | 1702 | self.setup(dataOut = dataOut, n = n , removeDC=removeDC , **kwargs) |
|
|
1705 | 1703 | self.isConfig = True |
|
|
1706 | 1704 | |
|
|
1707 | 1705 | |
|
|
1708 | 1706 | data_power, data_intensity, data_velocity,data_snrPP,data_specwidth,data_ccf, avgdatatime = self.pulsePairOp(dataOut, n, dataOut.utctime) |
|
|
1709 | 1707 | |
|
|
1710 | 1708 | |
|
|
1711 | 1709 | dataOut.flagNoData = True |
|
|
1712 | 1710 | |
|
|
1713 | 1711 | if self.__dataReady: |
|
|
1714 | 1712 | ###print("READY ----------------------------------") |
|
|
1715 | 1713 | dataOut.nCohInt *= self.n |
|
|
1716 | 1714 | dataOut.dataPP_POW = data_intensity # S |
|
|
1717 | 1715 | dataOut.dataPP_POWER = data_power # P valor que corresponde a POTENCIA MOMENTO |
|
|
1718 | 1716 | dataOut.dataPP_DOP = data_velocity |
|
|
1719 | 1717 | dataOut.dataPP_SNR = data_snrPP |
|
|
1720 | 1718 | dataOut.dataPP_WIDTH = data_specwidth |
|
|
1721 | 1719 | dataOut.dataPP_CCF = data_ccf |
|
|
1722 | 1720 | dataOut.PRFbyAngle = self.n #numero de PRF*cada angulo rotado que equivale a un tiempo. |
|
|
1723 | 1721 | dataOut.nProfiles = int(dataOut.nProfiles/n) |
|
|
1724 | 1722 | dataOut.utctime = avgdatatime |
|
|
1725 | 1723 | dataOut.flagNoData = False |
|
|
1726 | 1724 | return dataOut |
|
|
1727 | 1725 | |
|
|
1728 | 1726 | # import collections |
|
|
1729 | 1727 | # from scipy.stats import mode |
|
|
1730 | 1728 | # |
|
|
1731 | 1729 | # class Synchronize(Operation): |
|
|
1732 | 1730 | # |
|
|
1733 | 1731 | # isConfig = False |
|
|
1734 | 1732 | # __profIndex = 0 |
|
|
1735 | 1733 | # |
|
|
1736 | 1734 | # def __init__(self, **kwargs): |
|
|
1737 | 1735 | # |
|
|
1738 | 1736 | # Operation.__init__(self, **kwargs) |
|
|
1739 | 1737 | # # self.isConfig = False |
|
|
1740 | 1738 | # self.__powBuffer = None |
|
|
1741 | 1739 | # self.__startIndex = 0 |
|
|
1742 | 1740 | # self.__pulseFound = False |
|
|
1743 | 1741 | # |
|
|
1744 | 1742 | # def __findTxPulse(self, dataOut, channel=0, pulse_with = None): |
|
|
1745 | 1743 | # |
|
|
1746 | 1744 | # #Read data |
|
|
1747 | 1745 | # |
|
|
1748 | 1746 | # powerdB = dataOut.getPower(channel = channel) |
|
|
1749 | 1747 | # noisedB = dataOut.getNoise(channel = channel)[0] |
|
|
1750 | 1748 | # |
|
|
1751 | 1749 | # self.__powBuffer.extend(powerdB.flatten()) |
|
|
1752 | 1750 | # |
|
|
1753 | 1751 | # dataArray = numpy.array(self.__powBuffer) |
|
|
1754 | 1752 | # |
|
|
1755 | 1753 | # filteredPower = numpy.correlate(dataArray, dataArray[0:self.__nSamples], "same") |
|
|
1756 | 1754 | # |
|
|
1757 | 1755 | # maxValue = numpy.nanmax(filteredPower) |
|
|
1758 | 1756 | # |
|
|
1759 | 1757 | # if maxValue < noisedB + 10: |
|
|
1760 | 1758 | # #No se encuentra ningun pulso de transmision |
|
|
1761 | 1759 | # return None |
|
|
1762 | 1760 | # |
|
|
1763 | 1761 | # maxValuesIndex = numpy.where(filteredPower > maxValue - 0.1*abs(maxValue))[0] |
|
|
1764 | 1762 | # |
|
|
1765 | 1763 | # if len(maxValuesIndex) < 2: |
|
|
1766 | 1764 | # #Solo se encontro un solo pulso de transmision de un baudio, esperando por el siguiente TX |
|
|
1767 | 1765 | # return None |
|
|
1768 | 1766 | # |
|
|
1769 | 1767 | # phasedMaxValuesIndex = maxValuesIndex - self.__nSamples |
|
|
1770 | 1768 | # |
|
|
1771 | 1769 | # #Seleccionar solo valores con un espaciamiento de nSamples |
|
|
1772 | 1770 | # pulseIndex = numpy.intersect1d(maxValuesIndex, phasedMaxValuesIndex) |
|
|
1773 | 1771 | # |
|
|
1774 | 1772 | # if len(pulseIndex) < 2: |
|
|
1775 | 1773 | # #Solo se encontro un pulso de transmision con ancho mayor a 1 |
|
|
1776 | 1774 | # return None |
|
|
1777 | 1775 | # |
|
|
1778 | 1776 | # spacing = pulseIndex[1:] - pulseIndex[:-1] |
|
|
1779 | 1777 | # |
|
|
1780 | 1778 | # #remover senales que se distancien menos de 10 unidades o muestras |
|
|
1781 | 1779 | # #(No deberian existir IPP menor a 10 unidades) |
|
|
1782 | 1780 | # |
|
|
1783 | 1781 | # realIndex = numpy.where(spacing > 10 )[0] |
|
|
1784 | 1782 | # |
|
|
1785 | 1783 | # if len(realIndex) < 2: |
|
|
1786 | 1784 | # #Solo se encontro un pulso de transmision con ancho mayor a 1 |
|
|
1787 | 1785 | # return None |
|
|
1788 | 1786 | # |
|
|
1789 | 1787 | # #Eliminar pulsos anchos (deja solo la diferencia entre IPPs) |
|
|
1790 | 1788 | # realPulseIndex = pulseIndex[realIndex] |
|
|
1791 | 1789 | # |
|
|
1792 | 1790 | # period = mode(realPulseIndex[1:] - realPulseIndex[:-1])[0][0] |
|
|
1793 | 1791 | # |
|
|
1794 | 1792 | # print "IPP = %d samples" %period |
|
|
1795 | 1793 | # |
|
|
1796 | 1794 | # self.__newNSamples = dataOut.nHeights #int(period) |
|
|
1797 | 1795 | # self.__startIndex = int(realPulseIndex[0]) |
|
|
1798 | 1796 | # |
|
|
1799 | 1797 | # return 1 |
|
|
1800 | 1798 | # |
|
|
1801 | 1799 | # |
|
|
1802 | 1800 | # def setup(self, nSamples, nChannels, buffer_size = 4): |
|
|
1803 | 1801 | # |
|
|
1804 | 1802 | # self.__powBuffer = collections.deque(numpy.zeros( buffer_size*nSamples,dtype=numpy.float), |
|
|
1805 | 1803 | # maxlen = buffer_size*nSamples) |
|
|
1806 | 1804 | # |
|
|
1807 | 1805 | # bufferList = [] |
|
|
1808 | 1806 | # |
|
|
1809 | 1807 | # for i in range(nChannels): |
|
|
1810 | 1808 | # bufferByChannel = collections.deque(numpy.zeros( buffer_size*nSamples, dtype=numpy.complex) + numpy.NAN, |
|
|
1811 | 1809 | # maxlen = buffer_size*nSamples) |
|
|
1812 | 1810 | # |
|
|
1813 | 1811 | # bufferList.append(bufferByChannel) |
|
|
1814 | 1812 | # |
|
|
1815 | 1813 | # self.__nSamples = nSamples |
|
|
1816 | 1814 | # self.__nChannels = nChannels |
|
|
1817 | 1815 | # self.__bufferList = bufferList |
|
|
1818 | 1816 | # |
|
|
1819 | 1817 | # def run(self, dataOut, channel = 0): |
|
|
1820 | 1818 | # |
|
|
1821 | 1819 | # if not self.isConfig: |
|
|
1822 | 1820 | # nSamples = dataOut.nHeights |
|
|
1823 | 1821 | # nChannels = dataOut.nChannels |
|
|
1824 | 1822 | # self.setup(nSamples, nChannels) |
|
|
1825 | 1823 | # self.isConfig = True |
|
|
1826 | 1824 | # |
|
|
1827 | 1825 | # #Append new data to internal buffer |
|
|
1828 | 1826 | # for thisChannel in range(self.__nChannels): |
|
|
1829 | 1827 | # bufferByChannel = self.__bufferList[thisChannel] |
|
|
1830 | 1828 | # bufferByChannel.extend(dataOut.data[thisChannel]) |
|
|
1831 | 1829 | # |
|
|
1832 | 1830 | # if self.__pulseFound: |
|
|
1833 | 1831 | # self.__startIndex -= self.__nSamples |
|
|
1834 | 1832 | # |
|
|
1835 | 1833 | # #Finding Tx Pulse |
|
|
1836 | 1834 | # if not self.__pulseFound: |
|
|
1837 | 1835 | # indexFound = self.__findTxPulse(dataOut, channel) |
|
|
1838 | 1836 | # |
|
|
1839 | 1837 | # if indexFound == None: |
|
|
1840 | 1838 | # dataOut.flagNoData = True |
|
|
1841 | 1839 | # return |
|
|
1842 | 1840 | # |
|
|
1843 | 1841 | # self.__arrayBuffer = numpy.zeros((self.__nChannels, self.__newNSamples), dtype = numpy.complex) |
|
|
1844 | 1842 | # self.__pulseFound = True |
|
|
1845 | 1843 | # self.__startIndex = indexFound |
|
|
1846 | 1844 | # |
|
|
1847 | 1845 | # #If pulse was found ... |
|
|
1848 | 1846 | # for thisChannel in range(self.__nChannels): |
|
|
1849 | 1847 | # bufferByChannel = self.__bufferList[thisChannel] |
|
|
1850 | 1848 | # #print self.__startIndex |
|
|
1851 | 1849 | # x = numpy.array(bufferByChannel) |
|
|
1852 | 1850 | # self.__arrayBuffer[thisChannel] = x[self.__startIndex:self.__startIndex+self.__newNSamples] |
|
|
1853 | 1851 | # |
|
|
1854 | 1852 | # deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] |
|
|
1855 | 1853 | # dataOut.heightList = numpy.arange(self.__newNSamples)*deltaHeight |
|
|
1856 | 1854 | # # dataOut.ippSeconds = (self.__newNSamples / deltaHeight)/1e6 |
|
|
1857 | 1855 | # |
|
|
1858 | 1856 | # dataOut.data = self.__arrayBuffer |
|
|
1859 | 1857 | # |
|
|
1860 | 1858 | # self.__startIndex += self.__newNSamples |
|
|
1861 | 1859 | # |
|
|
1862 | 1860 | # return |
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