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How to use sub_key method in hypothesis
Best Python code snippet using hypothesis
ECRad_Results.py
Source:ECRad_Results.py 
1'''2Created on Dec 7, 20203@author: Severin Denk4Restructuring of the old ECRadresults class. Uses the OMFit style approach where the parent class is a dictionary5'''6from Distribution_Classes import Distribution7import numpy as np8np.set_printoptions(threshold=10)9import os10from Global_Settings import globalsettings11from scipy.io import savemat, loadmat12from scipy import constants as cnst13from ECRad_Config import ECRadConfig14from ECRad_Scenario import ECRadScenario15from Ndarray_Helper import ndarray_math_operation, ndarray_check_for_None16from netCDF4 import Dataset17import sys18class ECRadResults(dict):19 def __init__(self, lastused=False):20 self.result_keys = ["Trad", "resonance", "ray", "BPD", "weights", "dimensions"]21 self.shapes = {}22 self.units = {}23 self.scales = {}24 self.xaxis_link = {}25 self.legend_entries = {}26 self.labels = {}27 self.sub_keys = {}28 self.graph_style = {}29 self.failed_keys = {}30 # Mode order is mixed, X, O31 self.sub_keys["Trad"] = ["Trad", "tau", "T", \32 "Trad_second", "tau_second", "T_second"]33 self.shapes["Trad"] = ["N_time", "N_mode_mix", "N_ch"]34 self.units["Trad"] = {"Trad":"keV", "tau":"", "T":"", \35 "Trad_second":"keV", "tau_second":"", "T_second":""}36 self.scales["Trad"] = {"Trad":1.e-3, "tau":1.0, "T":1.0, \37 "Trad_second":1.e-3, "tau_second":1.0, "T_second":1.0}38 self.xaxis_link["Trad"] = ["resonance" ,"Trad"]39 self.legend_entries["Trad"] = {"Trad":r"$T_" + globalsettings.mathrm + r"{rad}$", "tau":r"$\tau$", "T":r"$T$", \40 "Trad_second":r"$T_" + globalsettings.mathrm + r"{rad,2nd\,model}$", \41 "tau_second":r"$\tau_" + globalsettings.mathrm + r"{2nd\,model}$", "T_second":r"$T_" + globalsettings.mathrm + r"{2nd\,model}$"}42 self.labels["Trad"] = {"Trad":r"$T_" + globalsettings.mathrm + r"{rad}$", "tau":r"$\tau$", "T":r"$T$", \43 "Trad_second":r"$T_" + globalsettings.mathrm + r"{rad}$", "tau_second":r"$\tau$", "T_second":r"$T$"}44 self.graph_style["Trad"] = "point"45 self.sub_keys["resonance"] = ["s_cold", "R_cold", "z_cold", \46 "rhop_cold", "rhot_cold", "s_warm", "R_warm", \47 "z_warm", "rhop_warm", "rhot_warm", \48 "s_warm_second", "R_warm_second", \49 "z_warm_second", "rhop_warm_second", \50 "rhot_warm_second"]51 # You want the channel as the inner most index since you want to plot as a function of channel52 self.shapes["resonance"] = ["N_time", "N_mode_mix", "N_ch"]53 self.units["resonance"] = {}54 self.scales["resonance"] = {}55 for sub_key in self.sub_keys["resonance"]:56 if(sub_key.startswith("rho")):57 self.units["resonance"][sub_key] = ""58 else:59 self.units["resonance"][sub_key] = "m"60 self.scales["resonance"][sub_key] = 1.061 self.xaxis_link["resonance"] = ["Trad", "resonance"]62 self.legend_entries["resonance"] = {"s_cold":r"$s_" + globalsettings.mathrm + r"{cold}$", \63 "R_cold":r"$R_" + globalsettings.mathrm + r"{cold}$", \64 "z_cold":r"$z_" + globalsettings.mathrm + r"{cold}$", \65 "rhop_cold":r"$\rho_" + globalsettings.mathrm + r"{pol,cold}$", \66 "rhot_cold":r"$\rho_" + globalsettings.mathrm + r"{tor,cold}$", \67 "s_warm":r"$s_" + globalsettings.mathrm + r"{warm}$", \68 "R_warm":r"$R_" + globalsettings.mathrm + r"{warm}$", \69 "z_warm":r"$z_" + globalsettings.mathrm + r"{warm}$", \70 "rhop_warm":r"$\rho_" + globalsettings.mathrm + r"{pol,warm}$", \71 "rhot_warmd":r"$\rho_" + globalsettings.mathrm + r"{tor,warm}$", \72 "s_warm_second":r"$s_" + globalsettings.mathrm + r"{warm,\,2nd\,model}$", \73 "R_warm_second":r"$R_" + globalsettings.mathrm + r"{warm,\,2nd\,model}$", \74 "z_warm_second":r"$z_" + globalsettings.mathrm + r"{warm,\,2nd\,model}$", \75 "rhop_warm_second":r"$\rho_" + globalsettings.mathrm + r"{pol,warm,\,2nd\,model}$", \76 "rhot_warm_second":r"$\rho_" + globalsettings.mathrm + r"{tor,warm,\,2nd\,model}$"}77 self.labels["resonance"] = {"s_cold":r"$s_" + globalsettings.mathrm + r"{cold}$", \78 "R_cold":r"$R_" + globalsettings.mathrm + r"{cold}$", \79 "z_cold":r"$z_" + globalsettings.mathrm + r"{cold}$", \80 "rhop_cold":r"$\rho_" + globalsettings.mathrm + r"{pol,cold}$", \81 "rhot_cold":r"$\rho_" + globalsettings.mathrm + r"{tor,cold}$", \82 "s_warm":r"$s_" + globalsettings.mathrm + r"{warm}$", \83 "R_warm":r"$R_" + globalsettings.mathrm + r"{warm}$", \84 "z_warm":r"$z_" + globalsettings.mathrm + r"{warm}$", \85 "rhop_warm":r"$\rho_" + globalsettings.mathrm + r"{pol,warm}$", \86 "rhot_warmd":r"$\rho_" + globalsettings.mathrm + r"{tor,warm}$", \87 "s_warm_second":r"$s_" + globalsettings.mathrm + r"{warm}$", \88 "R_warm_second":r"$R_" + globalsettings.mathrm + r"{warm}$", \89 "z_warm_second":r"$z_" + globalsettings.mathrm + r"{warm}$", \90 "rhop_warm_second":r"$\rho_" + globalsettings.mathrm + r"{pol,warm}$", \91 "rhot_warm_second":r"$\rho_" + globalsettings.mathrm + r"{tor,warm}$"}92 self.graph_style["resonance"] = "point"93 self.sub_keys["ray"] = ["s", "x", "y", "R", "z", \94 "Nx", "Ny", "Nz", \95 "Bx", "By", "Bz", \96 "H", "N", "Nc", \97 "X", "Y", "rhop", "rhot" ,\98 "Te", "ne", \99 "theta", "BPD", \100 "BPD_second", 101 "Trad", "Trad_second", "em", \102 "em_second", "ab", \103 "ab_second", \104 "T", "T_second", \105 "v_g_perp"]106 self.shapes["ray"] = ["N_time", "N_ch", "N_mode", "N_ray", "N_LOS"]107 self.legend_entries["ray"] = {"s":r"$s$", "x":r"$x$", "y":r"$y$", "R":r"$R$", "z":r"$z$", \108 "Nx":r"$N_" + globalsettings.mathrm + r"{x}$", "Ny":r"$N_" + globalsettings.mathrm + r"{y}$", \109 "Nz":r"$N_" + globalsettings.mathrm + r"{z}$", "Bx":r"$B_" + globalsettings.mathrm + r"{x}$", \110 "By":r"$B_" + globalsettings.mathrm + r"{y}$", "Bz":r"$B_" + globalsettings.mathrm + r"{z}$", \111 "H":r"Hamiltonian", "N":r"$N_" + globalsettings.mathrm + r"{ray}$", \112 "Nc":r"$N_" + globalsettings.mathrm + r"{disp}$", "X":r"Stix Parameter $X$", \113 "Y":r"Stix Parameter $Y$", "rhop":r"$\rho_" + globalsettings.mathrm + r"{pol}$", \114 "rhot":r"$\rho_" + globalsettings.mathrm + r"{tor}$", "Te":r"$T_" + globalsettings.mathrm + r"{e}$", \115 "ne":r"$n_" + globalsettings.mathrm + r"{e}$", "theta":r"$\theta$", \116 "BPD":"BPD", "BPD_second":"BPD$_" + globalsettings.mathrm + r"{2nd\,model}$", \117 "Trad":r"$T_" + globalsettings.mathrm + r"{rad}$", "Trad_second":r"$T_" + globalsettings.mathrm + r"{rad,\,2nd\,model}}$", \118 "em":r"$j$", \119 "em_second":r"$j_{" + globalsettings.mathrm + r"{2nd\,model}}$", "ab":r"$\alpha$", \120 "ab_second":r"$\alpha_{" + globalsettings.mathrm + r"{2nd\,model}}$", "T":r"$\mathcal{T}$", \121 "T_second":r"$\mathcal{T}_{" + globalsettings.mathrm + r"{2nd\,model}}$", "v_g_perp":r"$v_{" + globalsettings.mathrm + r"{g},\perp}$"}122 self.labels["ray"] = {"s":r"$s$", "x":r"$x$", "y":r"$y$", "R":r"$R$", "z":r"$z$", \123 "Nx":r"$N_" + globalsettings.mathrm + r"{x}$", "Ny":r"$N_" + globalsettings.mathrm + r"{y}$", \124 "Nz":r"$N_" + globalsettings.mathrm + r"{z}$", "Bx":r"$B_" + globalsettings.mathrm + r"{x}$", \125 "By":r"$B_" + globalsettings.mathrm + r"{y}$", "Bz":r"$B_" + globalsettings.mathrm + r"{z}$", \126 "H":r"Hamiltonian", "N":r"$N_" + globalsettings.mathrm + r"{ray}$", \127 "Nc":r"$N_" + globalsettings.mathrm + r"{disp}$", "X":r"Stix Parameter $X$", \128 "Y":r"Stix Parameter $Y$", "rhop":r"$\rho_" + globalsettings.mathrm + r"{pol}$", \129 "rhot":r"$\rho_" + globalsettings.mathrm + r"{tor}$", "Te":r"$T_" + globalsettings.mathrm + r"{e}$", \130 "ne":r"$n_" + globalsettings.mathrm + r"{e}$", "theta":r"$\theta$", \131 "BPD":"BPD", "BPD_second":"BPD", \132 "Trad":r"$T_" + globalsettings.mathrm + r"{rad}$", "Trad_second":r"$T_" + globalsettings.mathrm + r"{rad}$", \133 "em":r"$j_\omega$", \134 "em_second":r"$j_\omega$", "ab":r"$\alpha_\omega$", \135 "ab_second":r"$\alpha_\omega$", "T":r"$\mathcal{T}_\omega$", \136 "T_second":r"$\mathcal{T}_\omega$", "v_g_perp":r"$v_{" + globalsettings.mathrm + r"{g},\perp}$"}137 self.units["ray"] = {"s":"m", "x":"m", "y":"m", "R":"m", "z":"m", \138 "Nx":"", "Ny":"", "Nz":"", \139 "Bx":"T", "By":"T", "Bz":"T", \140 "H":"", "N":"", "Nc":"", \141 "X":"", "Y":"", \142 "rhop":"", "rhot":"",\143 "Te":r"keV", "ne":r"$10^{19}$m$^{-3}$", \144 "theta":r"$^\circ$", "BPD":r"m$^{-1}$", \145 "BPD_second":r"m$^{-1}$", \146 "Trad":r"keV", "Trad_second":r"keV", \147 "em":r"nW m$^{-3}$", \148 "em_second":r"nW m$^{-3}$", "ab":r"m$^{-1}$", \149 "ab_second":r"m$^{-1}$", \150 "T":"", "T_second":"", \151 "v_g_perp":""}152 self.scales["ray"] = {"s":1, "x":1, "y":1, "R":1, "z":1, \153 "Nx":1, "Ny":1, "Nz":1, \154 "Bx":1, "By":1, "Bz":1, \155 "H":1, "N":1, "Nc":1, \156 "X":1, "Y":1, \157 "rhop":1, "rhot":1, \158 "Te":1.e-3, "ne":1.e-19, \159 "theta":np.rad2deg(1), "BPD":1, \160 "BPD_second":1, \161 "Trad":1.e-3, "Trad_second":1.e-3, \162 "em":1.e9, \163 "em_second":1.e9, "ab":1, \164 "ab_second":1, \165 "T":1, "T_second":1, \166 "v_g_perp":1.0/cnst.speed_of_light}167 self.xaxis_link["ray"] = ["ray"]168 self.graph_style["ray"] = "line"169 self.sub_keys["BPD"] = ["rhop", "rhot", "BPD", "BPD_second"]170 self.scales["BPD"] = {"rhop":1.0, "rhot":1.0, "BPD":1.0, "BPD_second":1.0}171 self.labels["BPD"] = {"rhop":r"$\rho_" + globalsettings.mathrm + r"{pol}$", "rhot":r"$\rho_" + globalsettings.mathrm + r"{tor}$", \172 "BPD":"BPD","BPD_second":"BPD"}173 self.legend_entries["BPD"] = {"rhop":r"$\rho_" + globalsettings.mathrm + r"{pol}$", "rhot":r"$\rho_" + globalsettings.mathrm + r"{tor}$", \174 "BPD":"BPD","BPD_second":"BPD$_" + globalsettings.mathrm + r"{2nd\,model}$"}175 self.units["BPD"] = {"rhop":"", "rhot":"", "BPD":"m$^{-1}$", \176 "BPD_second":"m$^{-1}$"}177 self.xaxis_link["BPD"] = ["BPD"]178 self.shapes["BPD"] = ["N_time", "N_ch", "N_mode_mix", "N_BPD"]179 self.graph_style["BPD"] = "line"180 self.sub_keys["weights"] = ["mode_frac", "mode_frac_second", "ray_weights", "freq_weights"]181 self.units["weights"] = {}182 self.scales["weights"] = {}183 self.graph_style["weights"] = "point"184 for sub_key in self.sub_keys["weights"]:185 self.units["weights"][sub_key] = r'$\%$'186 self.scales["weights"][sub_key] = 1.e2187 self.labels["weights"] = {"mode_frac":r"Mode contribution", "mode_frac_second":"Mode contribution", \188 "ray_weights":"ray weight","freq_weights":"frequency weight"}189 self.legend_entries["weights"] = {"mode_frac":r"Mode contribution", "mode_frac_second":"Mode contribution", \190 "ray_weights":"ray weight","freq_weights":"frequency weight"}191 # The weights have a lot of different shapes need to store those by sub_key192 self.shapes["mode_frac"] = ["N_time", "N_mode", "N_ch"]193 self.shapes["mode_frac_second"] = ["N_time", "N_mode", "N_ch"]194 self.shapes["ray_weights"] = ["N_time", "N_ch", "N_ray"]195 self.shapes["freq_weights"] = ["N_time", "N_ch", "N_freq"]196 self.xaxis_link["weights"] = ["weights"]197 self.graph_style["BPD"] = "line"198 self["git"] = {"ECRad":"Unknoiwn", "GUI":"Unknoiwn", "Pylib":"Unknoiwn"}199 self["types"] = {}200 for key in self.result_keys:201 if(key == 'dimensions'):202 self["types"][key] = "int"203 else:204 self["types"][key] = "float"205 for key in self.units.keys():206 for sub_key in self.units[key].keys():207 if(len(self.units[key][sub_key]) > 0):208 self.units[key][sub_key] = "[" + self.units[key][sub_key] + "]"209 self.reset(not lastused)210 def reset(self, noLoad=True, light=False):211 # Does not reset Config or Scenario212 self.status = 0213 self.edition = 0214 self.init = False215 # Edition of this result216 # Remains zero until the result is saved217 # Time of the results, should be identical to self.Scenario.plasma_dict["time"]218 # This holds the same information as the scenario219 self.modes = None220 self.comment = ""221 self["dimensions"] = {}222 self["dimensions"]["N_LOS"] = []223 self["git"] = {}224 for key in self.result_keys:225 if(key in ["dimensions"]):226 continue227 self.failed_keys[key] = []228 self[key] = {}229 if(key in self.sub_keys):230 for sub_key in self.sub_keys[key]:231 self[key][sub_key] = []232 if(not light):233 self.Config = ECRadConfig(noLoad=noLoad)234 self.Scenario = ECRadScenario(noLoad=noLoad)235 self.data_origin = None236 237 def load(self, filename):238 if(filename is not None):239 ext = os.path.splitext(filename)[1]240 if(ext == ".mat"):241 self.from_mat(filename=filename)242 elif(ext == ".nc"):243 self.from_netcdf(filename=filename)244 else:245 print("Extension " + ext + " is unknown")246 raise(ValueError)247 def tidy_up(self, autosave=True):248 if(self.status != 0):249 return250 # Put everything into numpy arrays251 for key in self.result_keys:252 if(key in ["dimensions", "git", "types"]):253 continue254 for sub_key in self.sub_keys[key]:255 self[key][sub_key] = np.array(self[key][sub_key])256 # Autosave results257 self["git"]["ECRad"] = np.genfromtxt(os.path.join(globalsettings.ECRadRoot, "id"), dtype=str).item()258 self["git"]["GUI"] = np.genfromtxt(os.path.join(globalsettings.ECRadGUIRoot, "id"), dtype=str).item()259 self["git"]["Pylib"] = np.genfromtxt(os.path.join(globalsettings.ECRadPylibRoot, "id"), dtype=str).item()260 self.data_origin = "ECRad"261 if(autosave):262 self.autosave()263 264 def autosave(self,filename=None):265 self.to_netcdf(filename)266 def get_shape(self, key, start=None, stop=None,i_time=None, \267 i_ch=None, i_mode=None, i_ray=None):268 shape = ()269 for dim_ref in self.shapes[key][start:stop]:270 if(np.isscalar(self["dimensions"][dim_ref])):271 shape += (self["dimensions"][dim_ref],)272 else:273 # Cannot use numpy indexing here because the time dimension 274 # will be appended as we go275 shape += (self["dimensions"][dim_ref][i_time][i_ch, i_mode, i_ray],)276 return shape277 278 def get_index_reference(self, key, sub_key, ndim, index):279 # Retrieves the value this particular index refers to280 # used in plotting to label graphs.281 # The routine formats the quantity and returns a string282 # Note that the index should have the shape corresponding to the requested quantity283 if(key != "weights"):284 dim_ref = self.shapes[key][ndim]285 else:286 dim_ref = self.shapes[sub_key][ndim]287 if(dim_ref == "N_time"):288 return r"$t = $ " + "{0:1.3f}".format(self.Scenario["time"][index[ndim]]) + " s"289 elif(dim_ref == "N_ch"):290 return r"$f = $ " + "{0:3.1f}".format(self.Scenario["diagnostic"]["f"][index[0]][index[ndim]]/1.e9) + " GHz" 291 elif(dim_ref in ["N_mode"]):292 if(self.Config["Physics"]["considered_modes"] == 1):293 return "X-mode"294 elif(self.Config["Physics"]["considered_modes"] == 2):295 return "O-mode"296 else:297 if(index[ndim] == 0):298 return "X-mode"299 else:300 return "O-mode"301 elif(dim_ref == "N_mode_mix"):302 if(self.Config["Physics"]["considered_modes"] < 3):303 return ""304 else:305 if(index[ndim] == 1):306 return "X-mode"307 elif(index[ndim] == 2):308 return "O-mode"309 else:310 return ""311 elif(dim_ref == "N_ray"):312 if(index[ndim] == 0):313 return ""314 else:315 return r"ray \#" + str(index[ndim] + 1)316 else:317 raise ValueError("ECRadResults.get_index_reference could unexpected dim ref " + key + " " + sub_key + " " + str(ndim))318 319 def set_dimensions(self):320 # Sets the dimensions from Scenario and Configself["dimensions"]["N_time"] = len(self.Scenario.plasma_dict["time"])321 self["dimensions"]["N_time"] = self.Scenario["dimensions"]["N_time"]322 self["dimensions"]["N_ray"] = self.Config["Physics"]["N_ray"]323 self["dimensions"]["N_freq"] = self.Config["Physics"]["N_freq"]324 self["dimensions"]["N_BPD"] = self.Config["Numerics"]["N_BPD"]325 self["dimensions"]["N_ch"] = self.Scenario["dimensions"]["N_ch"]326 if(self.Config["Physics"]["considered_modes"] > 2):327 self["dimensions"]["N_mode"] = 2328 self["dimensions"]["N_mode_mix"] = 3329 modes_mix = ["", "X", "O"]330 modes = ["X", "O"]331 else:332 self["dimensions"]["N_mode"] = 1333 self["dimensions"]["N_mode_mix"] = 1334 modes = ["X"]335 if(self.Config["Physics"]["considered_modes"] == 2):336 modes = ["O"]337 modes_mix = [""]338 self["dimensions"]["N_ch"] = self.Scenario["dimensions"]["N_ch"]339 return modes, modes_mix340 def from_mat(self, filename):341 try:342 mdict = loadmat(filename, chars_as_strings=True, squeeze_me=True)343 except IOError as e:344 print(e)345 print("Error: " + filename + " does not exist")346 return347 self.Config.from_mat(mdict=mdict)348 self.Scenario.from_mat(mdict=mdict, load_plasma_dict=True)349 self.edition = mdict["edition"]350 # We need to do this song and dance because351 # 3D equlibria use rho tor instead of rho pol352 # This was not clearly indicated in the old353 # .mat files, but the new result files distinguish this.354 # Further cases are marked with #3D rhot355 if(self.Scenario["plasma"]["eq_dim"] == 3):356 rho = "rhot"357 else:358 rho = "rhop"359 if("comment" in mdict):360 self.comment = mdict["comment"]361 try:362 if(type(self.comment) == np.ndarray):363 if(len(self.comment) > 0):364 self.comment = self.comment[0]365 else:366 self.comment = ""367 except Exception as e:368 print("Failed to parse comment")369 print(e)370 self.comment = ""371 modes, modes_mix = self.set_dimensions()372 for key in ["Trad"]:373 for sub_key in self.sub_keys[key]:374 self[key][sub_key] = np.zeros(self.get_shape(key))375 for i_mode, mode in enumerate(modes_mix):376 if(sub_key == "T"):377 self[key][sub_key] = np.exp(-self["Trad"]["tau"])378 continue379 elif(sub_key == "T_second"):380 self[key][sub_key] = np.exp(-self["Trad"]["tau_second"])381 continue382 mdict_key = sub_key.replace("second","comp")383 self[key][sub_key][...,i_mode,:] = mdict[mode+mdict_key].reshape(self.get_shape(key,stop=1) + \384 self.get_shape(key,start=2)) *1.e3385 if(self["dimensions"]["N_mode"] > 1):386 mode_info_printed = False387 # mode resolved resonances are not available in .mat files388 for key in ["resonance"]:389 for sub_key in self.sub_keys[key]:390 self[key][sub_key] = np.zeros(self.get_shape(key))391 if(sub_key.endswith("second")):392 formatted_key = sub_key + "ary"393 else:394 formatted_key = sub_key395 #3D rhot396 if(rho == "rhot" and sub_key.startswith("rhot")):397 formatted_key = formatted_key.replace("rhot","rhop")398 elif(rho == "rhot" and formatted_key.startswith("rhop")):399 continue400 try:401 self[key][sub_key][...,0,:] = mdict[formatted_key].reshape(self.get_shape(key,stop=1) + \402 self.get_shape(key,start=2))403 if(not mode_info_printed):404 print("INFO:: No mode specific resonances in .mat files. Using mixed modes for all resonances.")405 mode_info_printed = True406 for imode in range(1,3):407 self[key][sub_key][...,imode,:] = self[key][sub_key][...,0,:]408 except KeyError:409 print("INFO: Couldn't load " + sub_key + " from result file")410 else:411 for key in ["resonance"]:412 for sub_key in self.sub_keys[key]:413 if(sub_key.endswith("second")):414 formatted_key = sub_key + "ary"415 else:416 formatted_key = sub_key417 #3D rhot418 if(rho == "rhot" and sub_key.startswith("rhot")):419 formatted_key = formatted_key.replace("rhot","rhop")420 elif(rho == "rhot" and formatted_key.startswith("rhop")):421 continue422 try:423 self[key][sub_key] = mdict[formatted_key].reshape(self.get_shape(key))424 except KeyError:425 print("INFO: Couldn't load " + sub_key + " from result file")426 self["dimensions"]["N_LOS"] = np.zeros(self.get_shape("ray", 0, -1),dtype=np.int) 427 # We need to fix the shape of the mdict ray info428 key = "ray"429 for sub_key in self.sub_keys[key]:430 for mode in modes:431 if(sub_key in ["em", "ab", "T", "BPD", "Trad", "Trad_second",\432 "em_second", "ab_second", "T_second", "BPD_second"]):433 mdict_key = "ray_" + sub_key434 #3D rhot435 elif(sub_key == "rhot" and rho == "rhot"):436 mdict_key = "rhop"437 elif(sub_key == "rhop" and rho == "rhot"):438 continue439 else:440 mdict_key = sub_key441 if(mdict_key+mode not in mdict.keys()):442 print("Cannot find " + key + "/" + sub_key + " in .mat")443 if(sub_key not in self.failed_keys[key]):444 self.failed_keys[key].append(sub_key)445 continue446 if(self["dimensions"]["N_time"] == 1):447 mdict[mdict_key+mode] = np.expand_dims(mdict[mdict_key+mode], 0)448 if(self["dimensions"]["N_ch"] == 1):449 mdict[mdict_key+mode] = np.expand_dims(mdict[mdict_key+mode],1)450 if(self["dimensions"]["N_ray"] == 1):451 mdict[mdict_key+mode] = np.expand_dims(mdict[mdict_key+mode],2)452 for key in ["ray", "BPD"]:453 for sub_key in self.sub_keys[key]:454 sub_key_error_printed = False455 if(key == "BPD"):456 mdict_key = None457 #3D rhot458 if(sub_key == "rhot" and self.Scenario["plasma"]["eq_dim"] == 2):459 continue460 elif(sub_key == "rhop" and self.Scenario["plasma"]["eq_dim"] == 3):461 continue462 elif(sub_key == "rhot" and self.Scenario["plasma"]["eq_dim"] == 3):463 # The BPD axis is mislabeled for 3D equilibria. It should be rhot464 mdict_key = "BPD" + "rhop"465 if(mdict_key is None):466 if(sub_key in ["rhop", "rhot"]):467 mdict_key = "BPD" + sub_key468 else:469 mdict_key = sub_key470 if(mdict_key+mode not in mdict.keys()):471 print("INFO: Cannot load " + key + "/" + sub_key)472 if(sub_key not in self.failed_keys[key]):473 self.failed_keys[key].append(sub_key)474 continue475 self[key][sub_key] = np.zeros(self.get_shape(key))476 for i_mode, mode in enumerate(modes):477 self[key][sub_key][...,i_mode,:] = mdict[mdict_key+mode].reshape(self.get_shape(key,stop=-2) + \478 (self["dimensions"]["N_BPD"],))479 else:480 if(sub_key in ["em", "ab", "T", "BPD", \481 "em_second", "ab_second", "T_second", "BPD_second"]):482 mdict_key = "ray_" + sub_key483 #3D rhot484 elif(sub_key == "rhot" and rho == "rhot"):485 mdict_key = "rhop"486 elif(sub_key == "rhop" and rho == "rhot"):487 continue488 else:489 mdict_key = sub_key490 if(mdict_key+mode not in mdict.keys()):491 if(sub_key !="R"):492 print("INFO: Cannot load " + key + "/" + sub_key)493 if(sub_key not in self.failed_keys[key]):494 self.failed_keys[key].append(sub_key)495 continue496 self["ray"][sub_key] = []497 for i_time in range(self["dimensions"]["N_time"]):498 self["ray"][sub_key].append([])499 for i_ch in range(self["dimensions"]["N_ch"]):500 self["ray"][sub_key][i_time].append([])501 for i_mode, mode in enumerate(modes):502 self["ray"][sub_key][i_time][i_ch].append([])503 for i_ray in range(self["dimensions"]["N_ray"]):504 try:505 self["ray"][sub_key][i_time][i_ch][i_mode].append( \506 mdict[mdict_key+mode][i_time][i_ch][i_ray])507 self["dimensions"]["N_LOS"][i_time][i_ch][i_mode][i_ray] = \508 len(self["ray"][sub_key][i_time][i_ch][i_mode][i_ray])509 except IndexError:510 if(not sub_key_error_printed):511 print("INFO: Failed to load {0:s} {1:s}".format(key,sub_key))512 print("INFO: For time index {0:d} channel {1:d} mode index {2:d} ray {3:d}".format(513 i_time, i_ch, i_mode, i_ray))514 sub_key_error_printed = True515 self["ray"][sub_key][i_time][i_ch][i_mode].append([])516 self["dimensions"]["N_LOS"][i_time][i_ch][i_mode][i_ray] = 0517 # Convert to ragged np array518 self["ray"][sub_key] = np.array(self["ray"][sub_key], dtype=np.object)519 self["weights"]["ray_weights"] = mdict["ray_weights"]520 self["weights"]["freq_weights"] = mdict["ray_weights"]521 if(self.Config["Physics"]["considered_modes"] > 2):522 self["weights"]["mode_frac"] = np.zeros(self.get_shape("mode_frac"))523 self["weights"]["mode_frac_second"] = np.zeros(self.get_shape("mode_frac_second"))524 self["weights"]["mode_frac"][...,0,:] = mdict["X_mode_frac"].reshape(self.get_shape("mode_frac",stop=1) + \525 self.get_shape("mode_frac",start=2))526 self["weights"]["mode_frac_second"][...,0,:] = mdict["X_mode_frac_comp"].reshape(self.get_shape("mode_frac_second",stop=1) + \527 self.get_shape("mode_frac_second",start=2))528 self["weights"]["mode_frac"][...,1,:] = 1 - mdict["X_mode_frac"].reshape(self.get_shape("mode_frac",stop=1) + \529 self.get_shape("mode_frac",start=2))530 self["weights"]["mode_frac_second"][...,1,:] = 1 - mdict["X_mode_frac_comp"].reshape(self.get_shape("mode_frac_second",stop=1) + \531 self.get_shape("mode_frac_second",start=2))532 else:533 self["weights"]["mode_frac"] = np.ones(self.get_shape("mode_frac"))534 self["weights"]["mode_frac_second"] = np.ones(self.get_shape("mode_frac_second"))535 self["ray"]["R"] = np.zeros(self.get_shape("ray", stop=-1), dtype=np.object)536 print("INFO: Fixing missing ray/R.")537 for itime in range(self["dimensions"]["N_time"]):538 for ich in range(self["dimensions"]["N_ch"]):539 for imode in range(self["dimensions"]["N_mode"]):540 for iray in range(self["dimensions"]["N_ray"]):541 if(self["dimensions"]["N_LOS"][i_time][i_ch][i_mode][i_ray] > 0):542 self["ray"]["R"][itime,ich,imode,iray] = np.sqrt(self["ray"]["x"][itime,ich,imode,iray]**2 + \543 self["ray"]["y"][itime,ich,imode,iray]**2)544 # We fix R later so we do not need to delete it545 self.failed_keys["ray"].remove("R")546 self["git"]["ECRad"] = mdict["ECRad_git_tag"]547 self["git"]["GUI"] = mdict["ECRadGUI_git_tag"]548 self["git"]["Pylib"] = mdict["ECRadPylib_git_tag"]549 self.data_origin = filename550 self.init = True551 return True552 553 def get_default_filename_and_edition(self, scratch=False, ed=None):554 if(scratch):555 dir = self.Config["Execution"]["scratch_dir"]556 else:557 dir = self.Config["Execution"]["working_dir"]558 diag_str = ""559 for key in self.Scenario["used_diags_dict"]:560 diag_str += key561 if(ed is None):562 ed = 1563 filename = os.path.join(dir, "ECRad_{0:5d}_{1:s}_ed{2:d}.nc".format(self.Scenario["shot"], diag_str, ed))564 while(os.path.exists(filename)):565 ed += 1566 filename = os.path.join(dir, "ECRad_{0:5d}_{1:s}_ed{2:d}.nc".format(self.Scenario["shot"], diag_str, ed))567 return filename, ed568 else:569 filename = os.path.join(dir, "ECRad_Results_{0:d}.nc".format(ed))570 return filename, 0571 def to_netcdf(self, filename=None, scratch=False, ed=None):572 if(filename is not None):573 rootgrp = Dataset(filename, "w", format="NETCDF4")574 else:575 filename, self.edition = self.get_default_filename_and_edition(scratch, ed=ed)576 rootgrp = Dataset(filename, "w", format="NETCDF4")577 rootgrp.createGroup("Results")578 self.Config.to_netcdf(rootgrp=rootgrp)579 self.Scenario.to_netcdf(rootgrp=rootgrp)580 for sub_key in self["dimensions"].keys():581 if(np.isscalar(self["dimensions"][sub_key])):582 rootgrp["Results"].createDimension(sub_key, self["dimensions"][sub_key])583 else:584 rootgrp["Results"].createDimension(sub_key, None) 585 for key in self.result_keys:586 if(key == "dimensions" or key == "ray"):587 continue588 dtype = "f8"589 if(self["types"][key] != "float"):590 dtype = "i8"591 try:592 for sub_key in self.sub_keys[key]:593 if(len(self[key][sub_key]) == 0):594 print("INFO: Not saving " + key + " " + sub_key + " because there is no data.")595 continue596 if(sub_key in self.failed_keys[key]):597 continue598 if(sub_key == "rhot" and self.Scenario["plasma"]["eq_dim"] == 2):599 continue600 elif(sub_key == "rhop" and self.Scenario["plasma"]["eq_dim"] == 3):601 continue602 if(key != "weights"):603 var = rootgrp["Results"].createVariable(key + "_" + sub_key,dtype, tuple(self.shapes[key]))604 else:605 var = rootgrp["Results"].createVariable(key + "_" + sub_key,dtype, tuple(self.shapes[sub_key]))606 var[:] = self[key][sub_key]607 except Exception as e:608 print(key, sub_key)609 raise e610 key = "ray"611 for sub_key in self.sub_keys["ray"]:612 if(sub_key in self.failed_keys[key]):613 continue614 elif(len(self[key][sub_key]) == 0):615 continue616 var = rootgrp["Results"].createVariable(key + "_" + sub_key,dtype, tuple(self.shapes[key]))617 for i_time in range(self["dimensions"]["N_time"]):618 for i_ch in range(self["dimensions"]["N_ch"]):619 for i_mode in range(self["dimensions"]["N_mode"]):620 for i_ray in range(self["dimensions"]["N_ray"]):621 var[i_time,i_ch,i_mode,i_ray,:] = self[key][sub_key][i_time,i_ch,i_mode,i_ray]622 # Get the shape information of the individual LOS length into the NETCDF file623 var = rootgrp["Results"].createVariable("dimensions" + "_" + "N_LOS", "i8", self.shapes["ray"][:-1])624 var[:] = self["dimensions"]["N_LOS"]625 rootgrp["Results"].comment = self.comment626 rootgrp["Results"].edition = self.edition627 rootgrp["Results"].ECRad_git_tag = self["git"]["ECRad"]628 rootgrp["Results"].ECRadGUI_git_tag = self["git"]["GUI"]629 rootgrp["Results"].ECRadPylib_git_tag = self["git"]["Pylib"]630 rootgrp.close()631 print("Created " + filename)632 633 def from_netcdf(self, filename):634 rootgrp = Dataset(filename, "r", format="NETCDF4")635 self.Config.from_netcdf(rootgrp=rootgrp)636 self.Scenario.from_netcdf(rootgrp=rootgrp)637 for sub_key in rootgrp["Results"].dimensions.keys():638 self["dimensions"][sub_key] = rootgrp["Results"].dimensions[sub_key].size639 self["dimensions"]["N_LOS"] = np.array(rootgrp["Results"]["dimensions" + "_" + "N_LOS"])640 for key in self.result_keys:641 if(key == "dimensions" or key == "ray"):642 continue643 for sub_key in self.sub_keys[key]:644 if(key + "_" + sub_key not in rootgrp["Results"].variables.keys()):645 print("INFO: Could not find " + key + " " + sub_key + " in the result file.")646 self.failed_keys[key].append(sub_key)647 continue648 if(key == "BPD"):649 if(sub_key == "rhot" and self.Scenario["plasma"]["eq_dim"] == 2):650 continue651 elif(sub_key == "rhop" and self.Scenario["plasma"]["eq_dim"] == 3):652 continue653 self[key][sub_key] = np.array(rootgrp["Results"][key + "_" + sub_key])654 655 key = "ray"656 for sub_key in self.sub_keys["ray"]:657 self["ray"][sub_key] = []658 if(key + "_" + sub_key not in rootgrp["Results"].variables.keys()):659 print("INFO: Cannot load " + key + "/" + sub_key)660 self.failed_keys[key].append(sub_key)661 continue662 for i_time in range(self["dimensions"]["N_time"]):663 self["ray"][sub_key].append([])664 for i_ch in range(self["dimensions"]["N_ch"]):665 self["ray"][sub_key][i_time].append([])666 for i_mode in range(self["dimensions"]["N_mode"]):667 self["ray"][sub_key][i_time][i_ch].append([])668 for i_ray in range(self["dimensions"]["N_ray"]):669 self["ray"][sub_key][i_time][i_ch][i_mode].append( \670 rootgrp["Results"][key+ "_" +sub_key][i_time,i_ch,i_mode,i_ray,\671 :self["dimensions"]["N_LOS"][i_time,i_ch,i_mode,i_ray]])672 self["ray"][sub_key] = np.array(self["ray"][sub_key], dtype=np.object)673 # Get the shape information of the individual LOS length into the NETCDF file674 self.comment = rootgrp["Results"].comment 675 self.edition = rootgrp["Results"].edition676 self["git"]["ECRad"] = rootgrp["Results"].ECRad_git_tag677 self["git"]["GUI"] = rootgrp["Results"].ECRadGUI_git_tag678 self["git"]["Pylib"] = rootgrp["Results"].ECRadPylib_git_tag679 self.data_origin = filename680 rootgrp.close()681 682if(__name__ == "__main__"):683 res = ECRadResults()684# res.from_mat("/mnt/c/Users/Severin/ECRad/ECRad_33585_EXT_ed1.mat")685# res.to_netcdf("/mnt/c/Users/Severin/ECRad/ECRad_33585_EXT_ed1.nc")686#"/mnt/c/Users/Severin/ECRad_regression/AUGX3/ECRad_32934_EXT_ed1.nc"687 # res.from_mat("/mnt/c/Users/Severin/ECRad/ECRad_35662_EXT_ed8.mat")688 # res.to_netcdf("/mnt/c/Users/Severin/ECRad/ECRad_35662_EXT_ed8.nc")689# res.reset()690 res.from_netcdf("/mnt/c/Users/Severin/ECRad/HFS_LHCD/ECRad_147634_EXT_ed1.nc")691 res.Scenario["plasma"]["dist_obj"].plot_Te_ne()692# res.reset()693# res.from_mat("/mnt/c/Users/Severin/ECRad_regression/W7X/ECRad_20180823016002_EXT_ed19.mat")694# res.to_netcdf("/mnt/c/Users/Severin/ECRad_regression/W7X/ECRad_20180823016002_EXT_Scenario.nc")695# res.reset()...
ECRad_Config.py
Source:ECRad_Config.py
1# -*- coding: utf-8 -*-2import os3from scipy.io import loadmat, savemat4from netCDF4 import Dataset5class ECRadConfig(dict):6 def __init__(self, noLoad = False):7 self.default_config_file = os.path.join(os.path.expanduser("~"), ".ECRad_GUI_Default.nc")8 if(noLoad):9 self.reset()10 else:11 try:12 self.reset()13 self.load(filename=self.default_config_file, default=True)14 except IOError:15 self.reset()16 def reset(self):17 self.main_keys = ["Physics", "Execution", "Numerics"]18 self.sub_keys = {}19 for key in self.main_keys:20 self[key] = {}21 self.sub_keys["Physics"] = ["dstf", "raytracing", "ripple", \22 "weak_rel", "considered_modes", \23 "N_freq", "N_ray", \24 "ratio_for_3rd_harm", "tau_ignore", "mode_conv" ,\25 "reflec_X", "reflec_O", \26 "R_shift", "z_shift", \27 "use_ext_rays"]28 self.sub_keys["Execution"] = ["working_dir", "scratch_dir", "extra_output", \29 "debug", "batch", "parallel" , \30 "parallel_cores", "wall_time", \31 "vmem"]32 self.sub_keys["Numerics"] = ["large_ds", "small_ds", "max_points_svec" , \33 "N_BPD"]34 self["Physics"]["dstf"] = "Th"35 self["Physics"]["raytracing"] = True36 self["Physics"]["ripple"] = True37 self["Physics"]["weak_rel"] = True38 self["Physics"]["N_freq"] = 139 self["Physics"]["N_ray"] = 140 self["Physics"]["ratio_for_3rd_harm"] = 0.441 self["Physics"]["tau_ignore"] = 1.e-842 self["Physics"]["considered_modes"] = 143 # 1 -> Only X44 # 2 -> Only O45 # 3 -> Both46 self["Physics"]["mode_conv"] = 0.047 self["Physics"]["reflec_X"] = 0.948 self["Physics"]["reflec_O"] = 0.949 self["Physics"]["R_shift"] = 0.050 self["Physics"]["z_shift"] = 0.051 self["Physics"]["use_ext_rays"] = False52 self["Execution"]["working_dir"] = ""53 self["Execution"]["scratch_dir"] = ""54 self["Execution"]["extra_output"] = True55 self["Execution"]["debug"] = False56 self["Execution"]["batch"] = True57 self["Execution"]["parallel"] = True58 self["Execution"]["parallel_cores"] = 3259 self["Execution"]["wall_time"] = 2.060 self["Execution"]["vmem"] = 3200061 self["Numerics"]["large_ds"] = 2.5e-362 self["Numerics"]["small_ds"] = 2.5e-463 self["Numerics"]["max_points_svec"] = 2000064 self["Numerics"]["N_BPD"] = 200065 self.types = {"working_dir":str, "scratch_dir":str, "dstf":str, "extra_output": "b", 66 "debug": "b", "batch": "b", "parallel": "b", 67 "parallel_cores": "i8", "wall_time": "f8", 68 "vmem": "i8", "raytracing": "b", "ripple": "b", 69 "weak_rel": "b", "N_freq" : "i8", "N_ray": "i8", 70 "ratio_for_3rd_harm": "f8", "tau_ignore" :"f8", "considered_modes" : "i8", 71 "mode_conv" : "f8", "reflec_X" : "f8","reflec_O" : "f8", 72 "R_shift" : "f8","z_shift" : "f8","large_ds" : "f8",73 "small_ds" : "f8","max_points_svec" : "i8","use_ext_rays" : "b", 74 "N_BPD" : "i8"}75 self.nice_labels = {"working_dir":"Working dir.", "scratch_dir":"Scratch dir.","dstf":"Distribution type", "extra_output": "Extra output", 76 "debug": "Debug", "batch": "Batch", "parallel": "Parallel", 77 "parallel_cores": "# cores", "wall_time": "wall time [h]", 78 "vmem": "virtual memory [MB]", "raytracing": "Raytracing", "ripple": "Magn. field Ripple", 79 "weak_rel": "Relativistic cor. for rt.", "N_freq" : "# frequencies", "N_ray": "# rays", 80 "ratio_for_3rd_harm": "omega_c/omega w. 3rd", "tau_ignore": "tau threshhold for computation of alpha/j",81 "considered_modes" : "Modes to consider", 82 "mode_conv" : "mode conv. ratio", "reflec_X" : "Wall refl. coeff. X-mode", 83 "reflec_O" : "Wall refl. coeff. O-mode", "use_ext_rays" : "Use ext rays", 84 "R_shift" : "R shift [m]","z_shift" : "z shift [m]", "large_ds" : "Large step size [m]",85 "small_ds" : "Small step size [m]","max_points_svec" : "Max points on LOS", 86 "N_BPD" : "Points for BPD"}87 88 def load(self, filename=None, mdict=None, rootgrp=None, default=False):89 if(filename is not None):90 ext = os.path.splitext(filename)[1]91 if(ext == ".mat"):92 self.from_mat(path_in=filename)93 elif(ext == ".nc"):94 self.from_netcdf(filename=filename,default=default)95 else:96 print("Extension " + ext + " is unknown")97 raise(ValueError)98 elif(mdict is not None):99 self.from_mat(mdict)100 elif(rootgrp is not None):101 self.from_netcdf(rootgrp=rootgrp)102 103 def from_mat(self, mdict=None, path_in=None):104 ext_mdict = False105 temp_config = None106 if(mdict is not None or path_in is not None):107 if(path_in is not None):108 mdict = loadmat(path_in, chars_as_strings=True, squeeze_me=True)109 else:110 ext_mdict = True111 else:112 raise ValueError("Either filename or mdict must be present")113 self.reset()114 key = "Execution"115 for sub_key in ["working_dir", "scratch_dir"]:116 if(os.path.isdir(mdict[sub_key])):117 self[key][sub_key] = mdict[sub_key]118 elif(not ext_mdict):119 self[key][sub_key] = mdict[sub_key]120 else:121 print("Warning working dir not imported, since it is not a valid directory")122 print("Falling back to last used working directory")123 temp_config = ECRadConfig()124 self[key][sub_key] = temp_config[key][sub_key]125 for key in self.main_keys:126 for sub_key in self.sub_keys[key]:127 if(sub_key in ["working_dir", "scratch_dir"]):128 continue129 else:130 if(sub_key in mdict.keys()):131 self[key][sub_key] = mdict[sub_key]132 else:133 print("Could not find " + sub_key + " in config file.")134 if(path_in is None and not ext_mdict):135 print("Successfully loaded last used configuration")136 return137 138 def to_netcdf(self, filename=None, rootgrp=None):139 if(filename is not None):140 rootgrp = Dataset(filename, "w", format="NETCDF4")141 rootgrp.createGroup("Config")142 rootgrp["Config"].createDimension('str_dim', 1)143 for key in self.main_keys:144 for sub_key in self.sub_keys[key]:145 if(self.types[sub_key] == str):146 var = rootgrp["Config"].createVariable(key + "_" + sub_key, self.types[sub_key], 'str_dim')147 var[0] = self[key][sub_key]148 else:149 var = rootgrp["Config"].createVariable(key + "_" + sub_key, self.types[sub_key])150 var[...] = self[key][sub_key]151 if(filename is not None):152 rootgrp.close()153 154 def from_netcdf(self, filename=None, rootgrp=None, default=False):155 self.reset()156 if(filename is not None):157 rootgrp = Dataset(filename, "r", format="NETCDF4")158 key = "Execution"159 for sub_key in ["working_dir", "scratch_dir"]:160 if(os.path.isdir(rootgrp["Config"][key + "_" + sub_key][0])):161 self[key][sub_key] = rootgrp["Config"][key + "_" + sub_key][0]162 elif(not default):163 print("Warning " + sub_key + " not imported, since it is not a valid directory")164 print("Falling back to last used " + sub_key)165 temp_config = ECRadConfig()166 self[key][sub_key] = temp_config["Execution"][sub_key]167 else:168 continue169 for key in self.main_keys:170 for sub_key in self.sub_keys[key]:171 try:172 if(sub_key in ["working_dir", "scratch_dir"]):173 continue174 if(self.types[sub_key] == "b"):175 self[key][sub_key] = bool(rootgrp["Config"][key + "_" + sub_key][...])176 elif(self.types[sub_key] == str):177 self[key][sub_key] = rootgrp["Config"][key + "_" + sub_key][0]178 else:179 self[key][sub_key] = rootgrp["Config"][key + "_" + sub_key][...].item()180 except IndexError:181 print("ERROR: Cannot find {0:s} in Config file.".format(key + "/" + sub_key))182 print("INFO: Using default value.")183 if(filename is not None):184 rootgrp.close()185 def autosave(self):186 config_file = os.path.join(os.path.expanduser("~"), ".ECRad_GUI_Default.nc")187 self.to_netcdf(filename=config_file)188if(__name__ == "__main__"):189 newConf = ECRadConfig(noLoad=True)190 newConf.load( filename="/mnt/c/Users/Severin/ECRad_regression/AUGX3/ECRad_32934_EXT_ed1.nc")...
test_winreg.py
Source:test_winreg.py
1# Test the windows specific win32reg module.2# Only win32reg functions not hit here: FlushKey, LoadKey and SaveKey3from _winreg import *4import os, sys5from test_support import verify, have_unicode6test_key_name = "SOFTWARE\\Python Registry Test Key - Delete Me"7test_data = [8 ("Int Value", 45, REG_DWORD),9 ("String Val", "A string value", REG_SZ,),10 ("StringExpand", "The path is %path%", REG_EXPAND_SZ),11 ("Multi-string", ["Lots", "of", "string", "values"], REG_MULTI_SZ),12 ("Raw Data", ("binary"+chr(0)+"data"), REG_BINARY),13]14if have_unicode:15 test_data+=[16 (unicode("Unicode Val"), unicode("A Unicode value"), REG_SZ,),17 ("UnicodeExpand", unicode("The path is %path%"), REG_EXPAND_SZ),18 ("Multi-unicode", [unicode("Lots"), unicode("of"), unicode("unicode"), unicode("values")], REG_MULTI_SZ),19 ("Multi-mixed", [unicode("Unicode"), unicode("and"), "string", "values"],REG_MULTI_SZ),20 ]21def WriteTestData(root_key):22 # Set the default value for this key.23 SetValue(root_key, test_key_name, REG_SZ, "Default value")24 key = CreateKey(root_key, test_key_name)25 # Create a sub-key26 sub_key = CreateKey(key, "sub_key")27 # Give the sub-key some named values28 for value_name, value_data, value_type in test_data:29 SetValueEx(sub_key, value_name, 0, value_type, value_data)30 # Check we wrote as many items as we thought.31 nkeys, nvalues, since_mod = QueryInfoKey(key)32 verify(nkeys==1, "Not the correct number of sub keys")33 verify(nvalues==1, "Not the correct number of values")34 nkeys, nvalues, since_mod = QueryInfoKey(sub_key)35 verify(nkeys==0, "Not the correct number of sub keys")36 verify(nvalues==len(test_data), "Not the correct number of values")37 # Close this key this way...38 # (but before we do, copy the key as an integer - this allows39 # us to test that the key really gets closed).40 int_sub_key = int(sub_key)41 CloseKey(sub_key)42 try:43 QueryInfoKey(int_sub_key)44 raise RuntimeError, "It appears the CloseKey() function does not close the actual key!"45 except EnvironmentError:46 pass47 # ... and close that key that way :-)48 int_key = int(key)49 key.Close()50 try:51 QueryInfoKey(int_key)52 raise RuntimeError, "It appears the key.Close() function does not close the actual key!"53 except EnvironmentError:54 pass55def ReadTestData(root_key):56 # Check we can get default value for this key.57 val = QueryValue(root_key, test_key_name)58 verify(val=="Default value", "Registry didn't give back the correct value")59 key = OpenKey(root_key, test_key_name)60 # Read the sub-keys61 sub_key = OpenKey(key, "sub_key")62 # Check I can enumerate over the values.63 index = 064 while 1:65 try:66 data = EnumValue(sub_key, index)67 except EnvironmentError:68 break69 verify(data in test_data, "Didn't read back the correct test data")70 index = index + 171 verify(index==len(test_data), "Didn't read the correct number of items")72 # Check I can directly access each item73 for value_name, value_data, value_type in test_data:74 read_val, read_typ = QueryValueEx(sub_key, value_name)75 verify(read_val==value_data and read_typ == value_type, \76 "Could not directly read the value" )77 sub_key.Close()78 # Enumerate our main key.79 read_val = EnumKey(key, 0)80 verify(read_val == "sub_key", "Read subkey value wrong")81 try:82 EnumKey(key, 1)83 verify(0, "Was able to get a second key when I only have one!")84 except EnvironmentError:85 pass86 key.Close()87def DeleteTestData(root_key):88 key = OpenKey(root_key, test_key_name, 0, KEY_ALL_ACCESS)89 sub_key = OpenKey(key, "sub_key", 0, KEY_ALL_ACCESS)90 # It is not necessary to delete the values before deleting91 # the key (although subkeys must not exist). We delete them92 # manually just to prove we can :-)93 for value_name, value_data, value_type in test_data:94 DeleteValue(sub_key, value_name)95 nkeys, nvalues, since_mod = QueryInfoKey(sub_key)96 verify(nkeys==0 and nvalues==0, "subkey not empty before delete")97 sub_key.Close()98 DeleteKey(key, "sub_key")99 try:100 # Shouldnt be able to delete it twice!101 DeleteKey(key, "sub_key")102 verify(0, "Deleting the key twice succeeded")103 except EnvironmentError:104 pass105 key.Close()106 DeleteKey(root_key, test_key_name)107 # Opening should now fail!108 try:109 key = OpenKey(root_key, test_key_name)110 verify(0, "Could open the non-existent key")111 except WindowsError: # Use this error name this time112 pass113def TestAll(root_key):114 WriteTestData(root_key)115 ReadTestData(root_key)116 DeleteTestData(root_key)117# Test on my local machine.118TestAll(HKEY_CURRENT_USER)119print "Local registry tests worked"120try:121 remote_name = sys.argv[sys.argv.index("--remote")+1]122except (IndexError, ValueError):123 remote_name = None124if remote_name is not None:125 try:126 remote_key = ConnectRegistry(remote_name, HKEY_CURRENT_USER)127 except EnvironmentError, exc:128 print "Could not connect to the remote machine -", exc.strerror129 remote_key = None130 if remote_key is not None:131 TestAll(remote_key)132 print "Remote registry tests worked"133else:134 print "Remote registry calls can be tested using",...
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