def test_values(self): vals = [1, 0, True, False, 'string', '', ['a'], [], ('t',), (), pd.DataFrame(['val1']), pd.DataFrame([]), pd.Series(['s']), pd.Series([]), 3., np.nan] for num, val in enumerate(vals): res = cb.not_null(val) # all evens should be True, all odds should be False correct = (num % 2) == 0 self.assertEqual(correct, res) self.assertTrue(cb.not_null(0, False))
def test_values(self): vals = [ 1, 0, True, False, 'string', '', ['a'], [], ('t', ), (), pd.DataFrame(['val1']), pd.DataFrame([]), pd.Series(['s']), pd.Series([]), 3., np.nan ] for num, val in enumerate(vals): res = cb.not_null(val) # all evens should be True, all odds should be False correct = (num % 2) == 0 self.assertEqual(correct, res) self.assertTrue(cb.not_null(0, False))
def get_data(dtype, loc_name): """ Extract data of type dtype for location loc_name. Write tmp_dtype.txt files if possible. """ if cb.not_null(all_data[dtype], False): data_container = all_data[dtype] if loc_name == "./": data_df = data_container.df else: # awkward workaround for chars like "(" and "?" that break in regex try: data_df = data_container.df[data_container.df[ 'location'].astype(str).str.contains(loc_name, na=False)] except: #sre_constants.error: data_df = data_container.df[ data_container.df['location'] == loc_name] data = data_container.convert_to_pmag_data_list(df=data_df) res = data_container.write_magic_file( 'tmp_{}.txt'.format(dtype), df=data_df) if not res: return [], [] return data, data_df return [], []
def get_data(dtype, loc_name): """ Extract data of type dtype for location loc_name. Write tmp_dtype.txt files if possible. """ if cb.not_null(all_data[dtype]): data_container = all_data[dtype] data_df = data_container.df[data_container.df['location'] == loc_name] data = data_container.convert_to_pmag_data_list(df=data_df) res = data_container.write_magic_file( 'tmp_{}.txt'.format(dtype), df=data_df) if not res: return [] return data
def get_data(dtype, loc_name): """ Extract data of type dtype for location loc_name. Write tmp_dtype.txt files if possible. """ if cb.not_null(all_data[dtype], False): data_container = all_data[dtype] if loc_name == "./": data_df = data_container.df else: # awkward workaround for chars like "(" and "?" that break in regex try: data_df = data_container.df[data_container.df['location'].astype(str).str.contains(loc_name, na=False)] except: #sre_constants.error: data_df = data_container.df[data_container.df['location'] == loc_name] data = data_container.convert_to_pmag_data_list(df=data_df) res = data_container.write_magic_file('tmp_{}.txt'.format(dtype), df=data_df) if not res: return [] return data
def InitLocCheck(self): """ make an interactive grid in which users can edit locations """ # if there is a location without a name, name it 'unknown' self.contribution.rename_item('locations', 'nan', 'unknown') # propagate lat/lon values from sites table self.contribution.get_min_max_lat_lon() # propagate lithologies & geologic classes from sites table self.contribution.propagate_cols_up(['lithologies', 'geologic_classes'], 'locations', 'sites') res = self.contribution.propagate_min_max_up() if cb.not_null(res): self.contribution.propagate_cols_up(['age_unit'], 'locations', 'sites') # set up frame self.panel = wx.Panel(self, style=wx.SIMPLE_BORDER) self.grid_frame = grid_frame3.GridFrame(self.contribution, self.WD, 'locations', 'locations', self.panel, main_frame=self.main_frame) # redefine default 'save & exit grid' button to go to next dialog instead self.grid_frame.exitButton.SetLabel('Save and continue') grid = self.grid_frame.grid self.grid_frame.Bind(wx.EVT_BUTTON, lambda event: self.onContinue(event, grid, self.InitAgeCheck), self.grid_frame.exitButton) # add back button self.backButton = wx.Button(self.grid_frame.panel, id=-1, label='Back', name='back_btn') self.Bind(wx.EVT_BUTTON, lambda event: self.onbackButton(event, self.InitSiteCheck), self.backButton) self.grid_frame.main_btn_vbox.Add(self.backButton, flag=wx.ALL, border=5) # re-do fit self.grid_frame.do_fit(None, min_size=self.min_size) # center self.grid_frame.Centre() return
def main(): """ NAME make_magic_plots.py DESCRIPTION inspects magic directory for available plots. SYNTAX make_magic_plots.py [command line options] INPUT magic files OPTIONS -h prints help message and quits -f FILE specifies input file name -fmt [png,eps,svg,jpg,pdf] specify format, default is png """ if '-h' in sys.argv: print(main.__doc__) sys.exit() # reset log files for fname in ['log.txt', 'errors.txt']: f = os.path.join(os.getcwd(), fname) if os.path.exists(f): os.remove(f) dirlist = ['./'] dir_path = os.getcwd() # if '-fmt' in sys.argv: ind = sys.argv.index("-fmt") fmt = sys.argv[ind + 1] else: fmt = 'png' if '-f' in sys.argv: ind = sys.argv.index("-f") filelist = [sys.argv[ind + 1]] else: filelist = os.listdir(dir_path) ## initialize some variables samp_file = 'samples.txt' azimuth_key = 'azimuth' meas_file = 'measurements.txt' loc_key = 'location' loc_file = 'locations.txt' method_key = 'method_codes' dec_key = 'dir_dec' inc_key = 'dir_inc' tilt_corr_key = "dir_tilt_correction" aniso_tilt_corr_key = "aniso_tilt_correction" hyst_bcr_key = "hyst_bcr" hyst_mr_key = "hyst_mr_moment" hyst_ms_key = "hyst_ms_moment" hyst_bc_key = "hyst_bc" Mkeys = ['magnitude', 'magn_moment', 'magn_volume', 'magn_mass'] results_file = 'sites.txt' hyst_file = 'specimens.txt' aniso_file = 'specimens.txt' # create contribution and propagate data throughout con = cb.Contribution() con.propagate_location_to_measurements() con.propagate_location_to_specimens() con.propagate_location_to_samples() if not con.tables: print('-E- No MagIC tables could be found in this directory') error_log("No MagIC tables found") return # check to see if propagation worked, otherwise you can't plot by location lowest_table = None for table in con.ancestry: if table in con.tables: lowest_table = table break do_full_directory = False # check that locations propagated down to the lowest table in the contribution if 'location' in con.tables[lowest_table].df.columns: # are there any locations in the lowest table? if not all(con.tables[lowest_table].df['location'].isnull()): locs = con.tables['locations'].df.index.unique() lowest_locs = con.tables[lowest_table].df['location'].unique() incorrect_locs = set(lowest_locs).difference(set(locs)) # are they actual locations? if not incorrect_locs: info_log( 'location names propagated to {}'.format(lowest_table)) else: do_full_directory = True error_log('location names did not propagate fully to {} table'. format(lowest_table)) else: do_full_directory = True error_log( 'could not propagate location names down to {} table'.format( lowest_table)) else: do_full_directory = True error_log('could not propagate location names down to {} table'.format( lowest_table)) all_data = {} all_data['measurements'] = con.tables.get('measurements', None) all_data['specimens'] = con.tables.get('specimens', None) all_data['samples'] = con.tables.get('samples', None) all_data['sites'] = con.tables.get('sites', None) all_data['locations'] = con.tables.get('locations', None) locations = con.tables['locations'].df.index.unique() dirlist = [loc for loc in locations if cb.not_null(loc) and loc != 'nan'] if not dirlist: dirlist = ["./"] if do_full_directory: dirlist = ["./"] # plot the whole contribution as one location if dirlist == ["./"]: error_log('plotting the entire contribution as one location') for fname in os.listdir("."): if fname.endswith(".txt"): shutil.copy(fname, "tmp_" + fname) # if possible, go through all data by location # use tmp_*.txt files to separate out by location for loc in dirlist: print('\nworking on: ', loc) def get_data(dtype, loc_name): """ Extract data of type dtype for location loc_name. Write tmp_dtype.txt files if possible. """ if cb.not_null(all_data[dtype]): data_container = all_data[dtype] data_df = data_container.df[data_container.df['location'] == loc_name] data = data_container.convert_to_pmag_data_list(df=data_df) res = data_container.write_magic_file( 'tmp_{}.txt'.format(dtype), df=data_df) if not res: return [] return data meas_data = get_data('measurements', loc) spec_data = get_data('specimens', loc) samp_data = get_data('samples', loc) site_data = get_data('sites', loc) location_data = get_data('locations', loc) if loc == "./": # if you can't sort by location, do everything together try: meas_data = con.tables[ 'measurements'].convert_to_pmag_data_list() except KeyError: meas_data = None try: spec_data = con.tables['specimens'].convert_to_pmag_data_list() except KeyError: spec_data = None try: samp_data = con.tables['samples'].convert_to_pmag_data_list() except KeyError: samp_data = None try: site_data = con.tables['sites'].convert_to_pmag_data_list() except KeyError: site_data = None crd = 's' if samp_file in filelist: # find coordinate systems samps = samp_data file_type = "samples" # get all non blank sample orientations Srecs = pmag.get_dictitem(samps, azimuth_key, '', 'F') if len(Srecs) > 0: crd = 'g' print('using geographic coordinates') else: print('using specimen coordinates') else: if VERBOSE: print('-I- No sample data found') if meas_file in filelist: # start with measurement data print('working on measurements data') data = meas_data file_type = 'measurements' # looking for zeq_magic possibilities # get all non blank method codes AFZrecs = pmag.get_dictitem(data, method_key, 'LT-AF-Z', 'has') # get all non blank method codes TZrecs = pmag.get_dictitem(data, method_key, 'LT-T-Z', 'has') # get all non blank method codes MZrecs = pmag.get_dictitem(data, method_key, 'LT-M-Z', 'has') # get all dec measurements Drecs = pmag.get_dictitem(data, dec_key, '', 'F') # get all inc measurements Irecs = pmag.get_dictitem(data, inc_key, '', 'F') for key in Mkeys: Mrecs = pmag.get_dictitem(data, key, '', 'F') # get intensity data if len(Mrecs) > 0: break # potential for stepwise demag curves if len(AFZrecs) > 0 or len(TZrecs) > 0 or len(MZrecs) > 0 and len( Drecs) > 0 and len(Irecs) > 0 and len(Mrecs) > 0: CMD = 'zeq_magic.py -f tmp_measurements.txt -fsp tmp_specimens.txt -fsa tmp_samples.txt -fsi tmp_sites.txt -sav -fmt ' + fmt + ' -crd ' + crd print(CMD) info_log(CMD, loc) os.system(CMD) # looking for thellier_magic possibilities if len(pmag.get_dictitem(data, method_key, 'LP-PI-TRM', 'has')) > 0: CMD = 'thellier_magic.py -f tmp_measurements.txt -fsp tmp_specimens.txt -sav -fmt ' + fmt print(CMD) info_log(CMD, loc) os.system(CMD) # looking for hysteresis possibilities if len(pmag.get_dictitem(data, method_key, 'LP-HYS', 'has')) > 0: # find hyst experiments # check for reqd columns missing = check_for_reqd_cols(data, ['treat_temp']) if missing: error_log( 'LP-HYS method code present, but required column(s) [{}] missing' .format(", ".join(missing)), loc, "quick_hyst.py") else: CMD = 'quick_hyst.py -f tmp_measurements.txt -sav -fmt ' + fmt print(CMD) info_log(CMD, loc) os.system(CMD) # equal area plots of directional data # at measurment level (by specimen) if data: missing = check_for_reqd_cols(data, ['dir_dec', 'dir_inc']) if not missing: CMD = "eqarea_magic.py -f tmp_measurements.txt -obj spc -sav -no-tilt -fmt " + fmt print(CMD) os.system(CMD) info_log(CMD, loc, "eqarea_magic.py") else: if VERBOSE: print('-I- No measurement data found') # site data if results_file in filelist: print('-I- result file found', results_file) data = site_data file_type = 'sites' print('-I- working on site directions') print('number of datapoints: ', len(data), loc) dec_key = 'dir_dec' inc_key = 'dir_inc' int_key = 'int_abs' SiteDIs = pmag.get_dictitem(data, dec_key, "", 'F') # find decs SiteDIs = pmag.get_dictitem(SiteDIs, inc_key, "", 'F') # find decs and incs dir_data_found = len(SiteDIs) print('{} Dec/inc pairs found'.format(dir_data_found)) # only individual results - not poles # get only individual results (if result_type col is available) if SiteDIs: if 'result_type' in SiteDIs[0]: SiteDIs = pmag.get_dictitem(SiteDIs, 'result_type', 'i', 'has') # then convert tilt_corr_key to correct format old_SiteDIs = SiteDIs SiteDIs = [] for rec in old_SiteDIs: if tilt_corr_key not in rec: error_log( "Directional data found, but missing {}, can't plot directions" .format(tilt_corr_key), loc, "eqarea_magic.py") break if cb.is_null( rec[tilt_corr_key]) and rec[tilt_corr_key] != 0: rec[tilt_corr_key] = "" else: try: rec[tilt_corr_key] = str( int(float(rec[tilt_corr_key]))) except ValueError: rec[tilt_corr_key] = "" SiteDIs.append(rec) print('number of individual directions: ', len(SiteDIs)) # tilt corrected coordinates SiteDIs_t = pmag.get_dictitem(SiteDIs, tilt_corr_key, '100', 'T', float_to_int=True) print('number of tilt corrected directions: ', len(SiteDIs_t)) SiteDIs_g = pmag.get_dictitem( SiteDIs, tilt_corr_key, '0', 'T', float_to_int=True) # geographic coordinates print('number of geographic directions: ', len(SiteDIs_g)) SiteDIs_s = pmag.get_dictitem( SiteDIs, tilt_corr_key, '-1', 'T', float_to_int=True) # sample coordinates print('number of sample directions: ', len(SiteDIs_s)) SiteDIs_x = pmag.get_dictitem(SiteDIs, tilt_corr_key, '', 'T') # no coordinates print('number of no coordinates directions: ', len(SiteDIs_x)) if len(SiteDIs_t) > 0 or len(SiteDIs_g) > 0 or len( SiteDIs_s) > 0 or len(SiteDIs_x) > 0: CRD = "" if len(SiteDIs_t) > 0: CRD = ' -crd t' elif len(SiteDIs_g) > 0: CRD = ' -crd g' elif len(SiteDIs_s) > 0: CRD = ' -crd s' CMD = 'eqarea_magic.py -f tmp_sites.txt -fsp tmp_specimens.txt -fsa tmp_samples.txt -flo tmp_locations.txt -sav -fmt ' + fmt + CRD print(CMD) info_log(CMD, loc) os.system(CMD) else: if dir_data_found: error_log( '{} dec/inc pairs found, but no equal area plots were made' .format(dir_data_found), loc, "equarea_magic.py") # print('-I- working on VGP map') VGPs = pmag.get_dictitem(SiteDIs, 'vgp_lat', "", 'F') # are there any VGPs? if len(VGPs) > 0: # YES! CMD = 'vgpmap_magic.py -f tmp_sites.txt -prj moll -res c -sym ro 5 -sav -fmt png' print(CMD) info_log(CMD, loc, 'vgpmap_magic.py') os.system(CMD) else: print('-I- No vgps found') print('-I- Look for intensities') # is there any intensity data? if site_data: if int_key in site_data[0].keys(): # old way, wasn't working right: #CMD = 'magic_select.py -key ' + int_key + ' 0. has -F tmp1.txt -f tmp_sites.txt' Selection = pmag.get_dictkey(site_data, int_key, dtype="f") with open('intensities.txt', 'w') as out: for rec in Selection: if rec != 0: out.write(str(rec * 1e6) + "\n") histfile = 'LO:_' + loc + \ '_TY:_intensities_histogram:_.' + fmt # maybe run histplot.main here instead, so you can return an error message CMD = "histplot.py -b 1 -xlab 'Intensity (uT)' -sav -f intensities.txt -F " + histfile os.system(CMD) info_log(CMD, loc) print(CMD) else: print('-I- No intensities found') else: print('-I- No intensities found') ## if hyst_file in filelist: print('working on hysteresis', hyst_file) data = spec_data file_type = 'specimens' hdata = pmag.get_dictitem(data, hyst_bcr_key, '', 'F') hdata = pmag.get_dictitem(hdata, hyst_mr_key, '', 'F') hdata = pmag.get_dictitem(hdata, hyst_ms_key, '', 'F') # there are data for a dayplot hdata = pmag.get_dictitem(hdata, hyst_bc_key, '', 'F') if len(hdata) > 0: CMD = 'dayplot_magic.py -f tmp_specimens.txt -sav -fmt ' + fmt info_log(CMD, loc) print(CMD) else: print('no hysteresis data found') if aniso_file in filelist: # do anisotropy plots if possible print('working on anisotropy', aniso_file) data = spec_data file_type = 'specimens' # make sure there is some anisotropy data if not data: print('No anisotropy data found') elif 'aniso_s' not in data[0]: print('No anisotropy data found') else: # get specimen coordinates if aniso_tilt_corr_key not in data[0]: sdata = data else: sdata = pmag.get_dictitem(data, aniso_tilt_corr_key, '-1', 'T', float_to_int=True) # get specimen coordinates gdata = pmag.get_dictitem(data, aniso_tilt_corr_key, '0', 'T', float_to_int=True) # get specimen coordinates tdata = pmag.get_dictitem(data, aniso_tilt_corr_key, '100', 'T', float_to_int=True) CRD = "" CMD = 'aniso_magic.py -x -B -sav -fmt ' + fmt if len(sdata) > 3: CMD = CMD + ' -crd s' print(CMD) info_log(CMD, loc) os.system(CMD) if len(gdata) > 3: CMD = CMD + ' -crd g' print(CMD) info_log(CMD, loc) os.system(CMD) if len(tdata) > 3: CMD = CMD + ' -crd t' print(CMD) info_log(CMD, loc) os.system(CMD) # remove temporary files for fname in glob.glob('tmp*.txt'): os.remove(fname) try: os.remove('intensities.txt') except FileNotFoundError: pass if loc_file in filelist: data, file_type = pmag.magic_read(loc_file) # read in location data print('-I- working on pole map') poles = pmag.get_dictitem(data, 'pole_lat', "", 'F') # are there any poles? poles = pmag.get_dictitem(poles, 'pole_lon', "", 'F') # are there any poles? if len(poles) > 0: # YES! CMD = 'polemap_magic.py -sav -fmt png' print(CMD) info_log(CMD, "all locations", "polemap_magic.py") os.system(CMD) else: print('-I- No poles found')
def main(): """ NAME make_magic_plots.py DESCRIPTION inspects magic directory for available data and makes plots SYNTAX make_magic_plots.py [command line options] INPUT magic files OPTIONS -h prints help message and quits -f FILE specifies input file name -fmt [png,eps,svg,jpg,pdf] specify format, default is png """ if '-h' in sys.argv: print(main.__doc__) sys.exit() # reset log files for fname in ['log.txt', 'errors.txt']: f = os.path.join(os.getcwd(), fname) if os.path.exists(f): os.remove(f) image_recs = [] dirlist = ['./'] dir_path = os.getcwd() # if '-fmt' in sys.argv: ind = sys.argv.index("-fmt") fmt = sys.argv[ind + 1] else: fmt = 'png' if '-f' in sys.argv: ind = sys.argv.index("-f") filelist = [sys.argv[ind + 1]] else: filelist = os.listdir(dir_path) ## initialize some variables samp_file = 'samples.txt' meas_file = 'measurements.txt' #loc_key = 'location' loc_file = 'locations.txt' method_key = 'method_codes' dec_key = 'dir_dec' inc_key = 'dir_inc' tilt_corr_key = "dir_tilt_correction" aniso_tilt_corr_key = "aniso_tilt_correction" hyst_bcr_key = "hyst_bcr" hyst_mr_key = "hyst_mr_moment" hyst_ms_key = "hyst_ms_moment" hyst_bc_key = "hyst_bc" Mkeys = ['magnitude', 'magn_moment', 'magn_volume', 'magn_mass'] results_file = 'sites.txt' hyst_file = 'specimens.txt' aniso_file = 'specimens.txt' # create contribution and propagate data throughout full_con = cb.Contribution() full_con.propagate_location_to_measurements() full_con.propagate_location_to_specimens() full_con.propagate_location_to_samples() if not full_con.tables: print('-E- No MagIC tables could be found in this directory') error_log("No MagIC tables found") return # try to get the contribution id for error logging con_id = "" if 'contribution' in full_con.tables: if 'id' in full_con.tables['contribution'].df.columns: con_id = full_con.tables['contribution'].df.iloc[0]['id'] # check to see if propagation worked, otherwise you can't plot by location lowest_table = None for table in full_con.ancestry: if table in full_con.tables: lowest_table = table break do_full_directory = False # check that locations propagated down to the lowest table in the contribution if 'location' in full_con.tables[lowest_table].df.columns: if 'locations' not in full_con.tables: info_log( 'location names propagated to {}, but could not be validated'. format(lowest_table)) # are there any locations in the lowest table? elif not all(full_con.tables[lowest_table].df['location'].isnull()): locs = full_con.tables['locations'].df.index.unique() lowest_locs = full_con.tables[lowest_table].df['location'].unique() incorrect_locs = set(lowest_locs).difference(set(locs)) # are they actual locations? if not incorrect_locs: info_log( 'location names propagated to {}'.format(lowest_table)) else: do_full_directory = True error_log( 'location names did not propagate fully to {} table (looks like there are some naming inconsistencies between tables)' .format(lowest_table), con_id=con_id) else: do_full_directory = True error_log( 'could not propagate location names down to {} table'.format( lowest_table), con_id=con_id) else: do_full_directory = True error_log('could not propagate location names down to {} table'.format( lowest_table), con_id=con_id) all_data = {} all_data['measurements'] = full_con.tables.get('measurements', None) all_data['specimens'] = full_con.tables.get('specimens', None) all_data['samples'] = full_con.tables.get('samples', None) all_data['sites'] = full_con.tables.get('sites', None) all_data['locations'] = full_con.tables.get('locations', None) if 'locations' in full_con.tables: locations = full_con.tables['locations'].df.index.unique() else: locations = [''] dirlist = [ loc for loc in locations if cb.not_null(loc, False) and loc != 'nan' ] if not dirlist: dirlist = ["./"] if do_full_directory: dirlist = ["./"] # plot the whole contribution as one location if dirlist == ["./"]: error_log('plotting the entire contribution as one location', con_id=con_id) for fname in os.listdir("."): if fname.endswith(".txt"): shutil.copy(fname, "tmp_" + fname) # if possible, go through all data by location # use tmp_*.txt files to separate out by location for loc in dirlist: print('\nworking on: ', loc) def get_data(dtype, loc_name): """ Extract data of type dtype for location loc_name. Write tmp_dtype.txt files if possible. """ if cb.not_null(all_data[dtype], False): data_container = all_data[dtype] if loc_name == "./": data_df = data_container.df else: # awkward workaround for chars like "(" and "?" that break in regex try: data_df = data_container.df[data_container.df[ 'location'].astype(str).str.contains(loc_name, na=False)] except: #sre_constants.error: data_df = data_container.df[ data_container.df['location'] == loc_name] data = data_container.convert_to_pmag_data_list(df=data_df) res = data_container.write_magic_file( 'tmp_{}.txt'.format(dtype), df=data_df) if not res: return [], [] return data, data_df return [], [] meas_data, meas_df = get_data('measurements', loc) spec_data, spec_df = get_data('specimens', loc) samp_data, samp_df = get_data('samples', loc) site_data, site_df = get_data('sites', loc) loc_data, loc_df = get_data('locations', loc) con = cb.Contribution(read_tables=[]) con.tables['measurements'] = cb.MagicDataFrame(df=meas_df, dtype="measurements") con.tables['specimens'] = cb.MagicDataFrame(df=spec_df, dtype="specimens") con.tables['samples'] = cb.MagicDataFrame(df=samp_df, dtype="samples") con.tables['sites'] = cb.MagicDataFrame(df=site_df, dtype="sites") con.tables['locations'] = cb.MagicDataFrame(df=loc_df, dtype="locations") if loc == "./": # if you can't sort by location, do everything together con = full_con try: meas_data = con.tables[ 'measurements'].convert_to_pmag_data_list() except KeyError: meas_data = None try: spec_data = con.tables['specimens'].convert_to_pmag_data_list() except KeyError: spec_data = None try: samp_data = con.tables['samples'].convert_to_pmag_data_list() except KeyError: samp_data = None try: site_data = con.tables['sites'].convert_to_pmag_data_list() except KeyError: site_data = None crd = 's' if 'samples' in con.tables: if 'azimuth' in con.tables['samples'].df.columns: if any(con.tables['samples'].df['azimuth'].dropna()): crd = 'g' if crd == 's': print('using specimen coordinates') else: print('using geographic coordinates') if meas_file in filelist and meas_data: # start with measurement data print('working on plotting measurements data') data = meas_data file_type = 'measurements' # looking for zeq_magic possibilities # get all non blank method codes AFZrecs = pmag.get_dictitem(data, method_key, 'LT-AF-Z', 'has') # get all non blank method codes TZrecs = pmag.get_dictitem(data, method_key, 'LT-T-Z', 'has') # get all non blank method codes MZrecs = pmag.get_dictitem(data, method_key, 'LT-M-Z', 'has') # get all dec measurements Drecs = pmag.get_dictitem(data, dec_key, '', 'F') # get all inc measurements Irecs = pmag.get_dictitem(data, inc_key, '', 'F') for key in Mkeys: Mrecs = pmag.get_dictitem(data, key, '', 'F') # get intensity data if len(Mrecs) > 0: break # potential for stepwise demag curves if len(AFZrecs) > 0 or len(TZrecs) > 0 or len(MZrecs) > 0 and len( Drecs) > 0 and len(Irecs) > 0 and len(Mrecs) > 0: #CMD = 'zeq_magic.py -f tmp_measurements.txt -fsp tmp_specimens.txt -fsa tmp_samples.txt -fsi tmp_sites.txt -sav -fmt ' + fmt + ' -crd ' + crd + " -new" CMD = "ipmag.zeq_magic(crd={}, n_plots='all', contribution={}, image_records=True)".format( crd, con) print(CMD) info_log(CMD, loc) res, outfiles, zeq_images = ipmag.zeq_magic(crd=crd, n_plots='all', contribution=con, image_records=True) image_recs.extend(zeq_images) # looking for thellier_magic possibilities if len(pmag.get_dictitem(data, method_key, 'LP-PI-TRM', 'has')) > 0: #CMD = 'thellier_magic.py -f tmp_measurements.txt -fsp tmp_specimens.txt -sav -fmt ' + fmt CMD = "ipmag.thellier_magic(n_specs='all', fmt='png', contribution={}, image_records=True)".format( con) print(CMD) info_log(CMD, loc) res, outfiles, thellier_images = ipmag.thellier_magic( n_specs='all', fmt="png", contribution=con, image_records=True) image_recs.extend(thellier_images) # looking for hysteresis possibilities if len(pmag.get_dictitem(data, method_key, 'LP-HYS', 'has')) > 0: # find hyst experiments # check for reqd columns missing = check_for_reqd_cols(data, ['treat_temp']) if missing: error_log( 'LP-HYS method code present, but required column(s) [{}] missing' .format(", ".join(missing)), loc, "quick_hyst.py", con_id=con_id) else: #CMD = 'quick_hyst.py -f tmp_measurements.txt -sav -fmt ' + fmt CMD = "ipmag.quick_hyst(fmt='png', n_plots='all', contribution={}, image_records=True)".format( con) print(CMD) info_log(CMD, loc) res, outfiles, quick_hyst_recs = ipmag.quick_hyst( fmt="png", n_plots='all', contribution=con, image_records=True) image_recs.extend(quick_hyst_recs) # equal area plots of directional data # at measurement level (by specimen) if data: missing = check_for_reqd_cols(data, ['dir_dec', 'dir_inc']) if not missing: #CMD = "eqarea_magic.py -f tmp_measurements.txt -obj spc -sav -no-tilt -fmt " + fmt CMD = "ipmag.eqarea_magic(fmt='png', n_plots='all', ignore_tilt=True, plot_by='spc', contribution={}, source_table='measurements', image_records=True)".format( con) print(CMD) info_log(CMD, loc, "eqarea_magic.py") res, outfiles, eqarea_spc_images = ipmag.eqarea_magic( fmt="png", n_plots='all', ignore_tilt=True, plot_by="spc", contribution=con, source_table="measurements", image_records=True) image_recs.extend(eqarea_spc_images) else: if VERBOSE: print('-I- No measurement data found') # site data if results_file in filelist and site_data: print('-I- result file found', results_file) data = site_data file_type = 'sites' print('-I- working on site directions') print('number of datapoints: ', len(data), loc) dec_key = 'dir_dec' inc_key = 'dir_inc' int_key = 'int_abs' SiteDIs = pmag.get_dictitem(data, dec_key, "", 'F') # find decs SiteDIs = pmag.get_dictitem(SiteDIs, inc_key, "", 'F') # find decs and incs dir_data_found = len(SiteDIs) print('{} Dec/inc pairs found'.format(dir_data_found)) if SiteDIs: # then convert tilt_corr_key to correct format old_SiteDIs = SiteDIs SiteDIs = [] for rec in old_SiteDIs: if tilt_corr_key not in rec: rec[tilt_corr_key] = "0" # make sure tilt_corr_key is a correct format try: rec[tilt_corr_key] = str(int(float( rec[tilt_corr_key]))) except ValueError: rec[tilt_corr_key] = "0" SiteDIs.append(rec) print('number of individual directions: ', len(SiteDIs)) # tilt corrected coordinates SiteDIs_t = pmag.get_dictitem(SiteDIs, tilt_corr_key, '100', 'T', float_to_int=True) print('number of tilt corrected directions: ', len(SiteDIs_t)) SiteDIs_g = pmag.get_dictitem( SiteDIs, tilt_corr_key, '0', 'T', float_to_int=True) # geographic coordinates print('number of geographic directions: ', len(SiteDIs_g)) SiteDIs_s = pmag.get_dictitem( SiteDIs, tilt_corr_key, '-1', 'T', float_to_int=True) # sample coordinates print('number of sample directions: ', len(SiteDIs_s)) SiteDIs_x = pmag.get_dictitem(SiteDIs, tilt_corr_key, '', 'T') # no coordinates print('number of no coordinates directions: ', len(SiteDIs_x)) if len(SiteDIs_t) > 0 or len(SiteDIs_g) > 0 or len( SiteDIs_s) > 0 or len(SiteDIs_x) > 0: CRD = "" if len(SiteDIs_t) > 0: CRD = ' -crd t' crd = "t" elif len(SiteDIs_g) > 0: CRD = ' -crd g' crd = "g" elif len(SiteDIs_s) > 0: CRD = ' -crd s' crd = "s" #CMD = 'eqarea_magic.py -f tmp_sites.txt -fsp tmp_specimens.txt -fsa tmp_samples.txt -flo tmp_locations.txt -sav -fmt ' + fmt + CRD CMD = "ipmag.eqarea_magic(crd={}, fmt='png', n_plots='all', contribution={}, source_table='sites')".format( crd, con) print(CMD) info_log(CMD, loc) res, outfiles, eqarea_site_recs = ipmag.eqarea_magic( crd=crd, fmt="png", n_plots='all', contribution=con, source_table="sites", image_records=True) image_recs.extend(eqarea_site_recs) else: if dir_data_found: error_log( '{} dec/inc pairs found, but no equal area plots were made' .format(dir_data_found), loc, "equarea_magic.py", con_id=con_id) # print('-I- working on VGP map') VGPs = pmag.get_dictitem(SiteDIs, 'vgp_lat', "", 'F') # are there any VGPs? if len(VGPs) > 0: # YES! #CMD = 'vgpmap_magic.py -f tmp_sites.txt -prj moll -res c -sym ro 5 -sav -fmt png' CMD = "ipmag.vgpmap_magic(proj='moll', sym='ro', size=5, fmt='png', contribution={})".format( con) print(CMD) info_log(CMD, loc, 'vgpmap_magic.py') res, outfiles, vgpmap_recs = ipmag.vgpmap_magic( proj='moll', sym='ro', size=5, fmt="png", contribution=con, image_records=True) image_recs.extend(vgpmap_recs) else: print('-I- No vgps found') print('-I- Look for intensities') # is there any intensity data? if site_data: if int_key in site_data[0].keys(): # old way, wasn't working right: #CMD = 'magic_select.py -key ' + int_key + ' 0. has -F tmp1.txt -f tmp_sites.txt' Selection = pmag.get_dictkey(site_data, int_key, dtype="f") selection = [i * 1e6 for i in Selection if i != 0] loc = loc.replace(" ", "_") if loc == "./": loc_name = "" else: loc_name = loc histfile = 'LO:_' + loc_name + \ '_TY:_intensities_histogram:_.' + fmt CMD = "histplot.py -twin -b 1 -xlab 'Intensity (uT)' -sav -f intensities.txt -F " + histfile CMD = "ipmag.histplot(data=selection, outfile=histfile, xlab='Intensity (uT)', binsize=1, norm=-1, save_plots=True)".format( histfile) info_log(CMD, loc) print(CMD) ipmag.histplot(data=selection, outfile=histfile, xlab="Intensity (uT)", binsize=1, norm=-1, save_plots=True) histplot_rec = { 'file': histfile, 'type': 'Other', 'title': 'Intensity histogram', 'software_packages': version.version, 'keywords': "", 'timestamp': datetime.date.today().isoformat() } image_recs.append(histplot_rec) else: print('-I- No intensities found') else: print('-I- No intensities found') ## if hyst_file in filelist and spec_data: print('working on hysteresis', hyst_file) data = spec_data file_type = 'specimens' hdata = pmag.get_dictitem(data, hyst_bcr_key, '', 'F') hdata = pmag.get_dictitem(hdata, hyst_mr_key, '', 'F') hdata = pmag.get_dictitem(hdata, hyst_ms_key, '', 'F') # there are data for a dayplot hdata = pmag.get_dictitem(hdata, hyst_bc_key, '', 'F') if len(hdata) > 0: CMD = "ipmag.dayplot_magic(save=True, fmt='png', contribution={}, image_records=True)".format( con) info_log(CMD, loc) print(CMD) res, outfiles, dayplot_recs = ipmag.dayplot_magic( save=True, fmt='png', contribution=con, image_records=True) image_recs.extend(dayplot_recs) else: print('no hysteresis data found') if aniso_file in filelist and spec_data: # do anisotropy plots if possible print('working on anisotropy', aniso_file) data = spec_data file_type = 'specimens' # make sure there is some anisotropy data if not data: print('No anisotropy data found') elif 'aniso_s' not in data[0]: print('No anisotropy data found') else: # get specimen coordinates if aniso_tilt_corr_key not in data[0]: sdata = data else: sdata = pmag.get_dictitem(data, aniso_tilt_corr_key, '-1', 'T', float_to_int=True) # get specimen coordinates gdata = pmag.get_dictitem(data, aniso_tilt_corr_key, '0', 'T', float_to_int=True) # get specimen coordinates tdata = pmag.get_dictitem(data, aniso_tilt_corr_key, '100', 'T', float_to_int=True) if len(sdata) > 3: CMD = "ipmag.aniso_magic(iboot=0, ihext=1, crd='s', fmt='png', contribution={})".format( con) print(CMD) info_log(CMD, loc) res, files, aniso_recs = ipmag.aniso_magic( iboot=0, ihext=1, crd="s", fmt="png", contribution=con, image_records=True) image_recs.extend(aniso_recs) if len(gdata) > 3: CMD = "ipmag.aniso_magic(iboot=0, ihext=1, crd='g', fmt='png', contribution={})".format( con) print(CMD) info_log(CMD, loc) res, files, aniso_recs = ipmag.aniso_magic( iboot=0, ihext=1, crd="g", fmt="png", contribution=con, image_records=True) image_recs.extend(aniso_recs) if len(tdata) > 3: CMD = "ipmag.aniso_magic(iboot=0, ihext=1, crd='g', fmt='png', contribution={})".format( con) print(CMD) info_log(CMD, loc) res, files, aniso_recs = ipmag.aniso_magic( iboot=0, ihext=1, crd="t", fmt="png", contribution=con, image_records=True) image_recs.extend(aniso_recs) # remove temporary files for fname in glob.glob('tmp*.txt'): os.remove(fname) # now we need full contribution data if loc_file in filelist and loc_data: #data, file_type = pmag.magic_read(loc_file) # read in location data data = loc_data print('-I- working on pole map') poles = pmag.get_dictitem(data, 'pole_lat', "", 'F') # are there any poles? poles = pmag.get_dictitem(poles, 'pole_lon', "", 'F') # are there any poles? if len(poles) > 0: # YES! CMD = 'polemap_magic.py -sav -fmt png -rev gv 40' CMD = 'ipmag.polemap_magic(flip=True, rsym="gv", rsymsize=40, fmt="png", contribution={})'.format( full_con) print(CMD) info_log(CMD, "all locations", "polemap_magic.py") res, outfiles, polemap_recs = ipmag.polemap_magic( flip=True, rsym="gv", rsymsize=40, fmt="png", contribution=full_con, image_records=True) image_recs.extend(polemap_recs) else: print('-I- No poles found') if image_recs: new_image_file = os.path.join(dir_path, 'new_images.txt') old_image_file = os.path.join(dir_path, 'images.txt') pmag.magic_write(new_image_file, image_recs, 'images') if os.path.exists(old_image_file): ipmag.combine_magic([old_image_file, new_image_file], outfile=old_image_file, magic_table="images", dir_path=dir_path) else: os.rename(new_image_file, old_image_file) if set_env.isServer: thumbnails.make_thumbnails(dir_path)
def main(): """ NAME zeq_magic.py DESCRIPTION reads in magic_measurements formatted file, makes plots of remanence decay during demagnetization experiments. Reads in prior interpretations saved in a pmag_specimens formatted file [and allows re-interpretations of best-fit lines and planes and saves (revised or new) interpretations in a pmag_specimens file. interpretations are saved in the coordinate system used. Also allows judicious editting of measurements to eliminate "bad" measurements. These are marked as such in the magic_measurements input file. they are NOT deleted, just ignored. ] Bracketed part not yet implemented SYNTAX zeq_magic.py [command line options] OPTIONS -h prints help message and quits -f MEASFILE: sets measurements format input file, default: measurements.txt -fsp SPECFILE: sets specimens format file with prior interpreations, default: specimens.txt -fsa SAMPFILE: sets samples format file sample=>site information, default: samples.txt -fsi SITEFILE: sets sites format file with site=>location informationprior interpreations, default: samples.txt -Fp PLTFILE: sets filename for saved plot, default is name_type.fmt (where type is zijd, eqarea or decay curve) -crd [s,g,t]: sets coordinate system, g=geographic, t=tilt adjusted, default: specimen coordinate system -spc SPEC plots single specimen SPEC, saves plot with specified format with optional -dir settings and quits -dir [L,P,F][beg][end]: sets calculation type for principal component analysis, default is none beg: starting step for PCA calculation end: ending step for PCA calculation [L,P,F]: calculation type for line, plane or fisher mean must be used with -spc option -fmt FMT: set format of saved plot [png,svg,jpg] -A: suppresses averaging of replicate measurements, default is to average -sav: saves all plots without review SCREEN OUTPUT: Specimen, N, a95, StepMin, StepMax, Dec, Inc, calculation type """ # initialize some variables doave, e, b = 1, 0, 0 # average replicates, initial end and beginning step intlist = ['magn_moment', 'magn_volume', 'magn_mass', 'magnitude'] plots, coord = 0, 's' noorient = 0 version_num = pmag.get_version() verbose = pmagplotlib.verbose calculation_type, fmt = "", "svg" spec_keys = [] geo, tilt, ask = 0, 0, 0 PriorRecs = [] # empty list for prior interpretations backup = 0 specimen = "" # can skip everything and just plot one specimen with bounds e,b if '-h' in sys.argv: print(main.__doc__) sys.exit() dir_path = pmag.get_named_arg("-WD", default_val=os.getcwd()) meas_file = pmag.get_named_arg("-f", default_val="measurements.txt") spec_file = pmag.get_named_arg("-fsp", default_val="specimens.txt") samp_file = pmag.get_named_arg("-fsa", default_val="samples.txt") site_file = pmag.get_named_arg("-fsi", default_val="sites.txt") #meas_file = os.path.join(dir_path, meas_file) #spec_file = os.path.join(dir_path, spec_file) #samp_file = os.path.join(dir_path, samp_file) #site_file = os.path.join(dir_path, site_file) plot_file = pmag.get_named_arg("-Fp", default_val="") crd = pmag.get_named_arg("-crd", default_val="s") if crd == "s": coord = "-1" elif crd == "t": coord = "100" else: coord = "0" saved_coord = coord fmt = pmag.get_named_arg("-fmt", "svg") specimen = pmag.get_named_arg("-spc", default_val="") #if specimen: # just save plot and exit # plots, verbose = 1, 0 beg_pca, end_pca = "", "" if '-dir' in sys.argv: ind = sys.argv.index('-dir') direction_type = sys.argv[ind + 1] beg_pca = int(sys.argv[ind + 2]) end_pca = int(sys.argv[ind + 3]) if direction_type == 'L': calculation_type = 'DE-BFL' if direction_type == 'P': calculation_type = 'DE-BFP' if direction_type == 'F': calculation_type = 'DE-FM' if '-A' in sys.argv: doave = 0 if '-sav' in sys.argv: plots, verbose = 1, 0 # first_save = 1 fnames = { 'measurements': meas_file, 'specimens': spec_file, 'samples': samp_file, 'sites': site_file } contribution = cb.Contribution( dir_path, custom_filenames=fnames, read_tables=['measurements', 'specimens', 'samples', 'sites']) # # import specimens if 'measurements' not in contribution.tables: print('-W- No measurements table found in your working directory') return specimen_cols = [ 'analysts', 'aniso_ftest', 'aniso_ftest12', 'aniso_ftest23', 'aniso_s', 'aniso_s_mean', 'aniso_s_n_measurements', 'aniso_s_sigma', 'aniso_s_unit', 'aniso_tilt_correction', 'aniso_type', 'aniso_v1', 'aniso_v2', 'aniso_v3', 'citations', 'description', 'dir_alpha95', 'dir_comp', 'dir_dec', 'dir_inc', 'dir_mad_free', 'dir_n_measurements', 'dir_tilt_correction', 'experiments', 'geologic_classes', 'geologic_types', 'hyst_bc', 'hyst_bcr', 'hyst_mr_moment', 'hyst_ms_moment', 'int_abs', 'int_b', 'int_b_beta', 'int_b_sigma', 'int_corr', 'int_dang', 'int_drats', 'int_f', 'int_fvds', 'int_gamma', 'int_mad_free', 'int_md', 'int_n_measurements', 'int_n_ptrm', 'int_q', 'int_rsc', 'int_treat_dc_field', 'lithologies', 'meas_step_max', 'meas_step_min', 'meas_step_unit', 'method_codes', 'sample', 'software_packages', 'specimen' ] if 'specimens' in contribution.tables: contribution.propagate_name_down('sample', 'measurements') # add location/site info to measurements table for naming plots if pmagplotlib.isServer: contribution.propagate_name_down('site', 'measurements') contribution.propagate_name_down('location', 'measurements') spec_container = contribution.tables['specimens'] if 'method_codes' not in spec_container.df.columns: spec_container.df['method_codes'] = None prior_spec_data = spec_container.get_records_for_code( 'LP-DIR', strict_match=False ) # look up all prior directional interpretations # # tie sample names to measurement data # else: spec_container, prior_spec_data = None, [] # # import samples for orientation info # if 'samples' in contribution.tables: samp_container = contribution.tables['samples'] samps = samp_container.df samp_data = samps.to_dict( 'records' ) # convert to list of dictionaries for use with get_orient else: samp_data = [] #if ('samples' in contribution.tables) and ('specimens' in contribution.tables): # # contribution.propagate_name_down('site','measurements') # contribution.propagate_cols(col_names=[ # 'azimuth', 'dip', 'orientation_quality','bed_dip','bed_dip_direction'], target_df_name='measurements', source_df_name='samples') ## # define figure numbers for equal area, zijderveld, # and intensity vs. demagnetiztion step respectively # ZED = {} ZED['eqarea'], ZED['zijd'], ZED['demag'] = 1, 2, 3 pmagplotlib.plot_init(ZED['eqarea'], 6, 6) pmagplotlib.plot_init(ZED['zijd'], 6, 6) pmagplotlib.plot_init(ZED['demag'], 6, 6) # save_pca=0 angle, direction_type, setangle = "", "", 0 # create measurement dataframe # meas_container = contribution.tables['measurements'] meas_data = meas_container.df # meas_data = meas_data[meas_data['method_codes'].str.contains( 'LT-NO|LT-AF-Z|LT-T-Z|LT-M-Z') == True] # fish out steps for plotting meas_data = meas_data[meas_data['method_codes'].str.contains( 'AN|ARM|LP-TRM|LP-PI-ARM') == False] # strip out unwanted experiments intensity_types = [ col_name for col_name in meas_data.columns if col_name in intlist ] intensity_types = [ col_name for col_name in intensity_types if any(meas_data[col_name]) ] if not len(intensity_types): print('-W- No intensity columns found') return # plot first non-empty intensity method found - normalized to initial value anyway - # doesn't matter which used int_key = intensity_types[0] # get all the non-null intensity records of the same type meas_data = meas_data[meas_data[int_key].notnull()] if 'quality' not in meas_data.columns: meas_data['quality'] = 'g' # set the default flag to good # need to treat LP-NO specially for af data, treatment should be zero, # otherwise 273. #meas_data['treatment'] = meas_data['treat_ac_field'].where( # cond=meas_data['treat_ac_field'] != 0, other=meas_data['treat_temp']) meas_data['treatment'] = meas_data['treat_ac_field'].where( cond=meas_data['treat_ac_field'].astype(bool), other=meas_data['treat_temp']) meas_data['ZI'] = 1 # initialize these to one meas_data['instrument_codes'] = "" # initialize these to blank # for unusual case of microwave power.... if 'treat_mw_power' in meas_data.columns: meas_data.loc[ (meas_data.treat_mw_power != 0) & (meas_data.treat_mw_power) & (meas_data.treat_mw_time), 'treatment'] = meas_data.treat_mw_power * meas_data.treat_mw_time # # get list of unique specimen names from measurement data # # this is a list of all the specimen names specimen_names = meas_data.specimen.unique() specimen_names = specimen_names.tolist() specimen_names.sort() # # set up new DataFrame for this sessions specimen interpretations # data_container = cb.MagicDataFrame(dtype='specimens', columns=specimen_cols) # this is for interpretations from this session current_spec_data = data_container.df if specimen == "": k = 0 else: k = specimen_names.index(specimen) # let's look at the data now while k < len(specimen_names): mpars = {"specimen_direction_type": "Error"} # set the current specimen for plotting this_specimen = specimen_names[k] # reset beginning/end pca if plotting more than one specimen if not specimen: beg_pca, end_pca = "", "" if verbose and this_specimen != "": print(this_specimen, k + 1, 'out of ', len(specimen_names)) if setangle == 0: angle = "" this_specimen_measurements = meas_data[ meas_data['specimen'].str.contains(this_specimen).astype( bool)] # fish out this specimen this_specimen_measurements = this_specimen_measurements[ -this_specimen_measurements['quality'].str.contains('b').astype( bool)] # remove bad measurements if len(this_specimen_measurements) != 0: # if there are measurements meas_list = this_specimen_measurements.to_dict( 'records') # get a list of dictionaries this_sample = "" if coord != '-1' and 'sample' in meas_list[0].keys( ): # look up sample name this_sample = pmag.get_dictitem(meas_list, 'specimen', this_specimen, 'T') if len(this_sample) > 0: this_sample = this_sample[0]['sample'] # # set up datablock [[treatment,dec, inc, int, direction_type],[....]] # # # figure out the method codes # units, methods, title = "", "", this_specimen if pmagplotlib.isServer: try: loc = this_specimen_measurements.loc[:, 'location'].values[0] except: loc = "" try: site = this_specimen_measurements.loc[:, 'site'].values[0] except: site = "" try: samp = this_specimen_measurements.loc[:, 'sample'].values[0] except: samp = "" title = "LO:_{}_SI:_{}_SA:_{}_SP:_{}_".format( loc, site, samp, this_specimen) # this is a list of all the specimen method codes meas_meths = this_specimen_measurements.method_codes.unique() tr = pd.to_numeric(this_specimen_measurements.treatment).tolist() if any(cb.is_null(treat, False) for treat in tr): print( '-W- Missing required values in measurements.treatment for {}, skipping' .format(this_specimen)) if specimen: return k += 1 continue if set(tr) == set([0]): print( '-W- Missing required values in measurements.treatment for {}, skipping' .format(this_specimen)) if specimen: return k += 1 continue for m in meas_meths: if 'LT-AF-Z' in m and 'T' not in units: units = 'T' # units include tesla tr[0] = 0 if 'LT-T-Z' in m and 'K' not in units: units = units + ":K" # units include kelvin if 'LT-M-Z' in m and 'J' not in units: units = units + ':J' # units include joules tr[0] = 0 units = units.strip(':') # strip off extra colons if 'LP-' in m: methods = methods + ":" + m decs = pd.to_numeric(this_specimen_measurements.dir_dec).tolist() incs = pd.to_numeric(this_specimen_measurements.dir_inc).tolist() # # fix the coordinate system # # revert to original coordinate system coord = saved_coord if coord != '-1': # need to transform coordinates to geographic # get the azimuth or_info, az_type = pmag.get_orient(samp_data, this_sample, data_model=3) if 'azimuth' in or_info.keys() and cb.not_null( or_info['azimuth']): #azimuths = pd.to_numeric( # this_specimen_measurements.azimuth).tolist() #dips = pd.to_numeric(this_specimen_measurements.dip).tolist() azimuths = len(decs) * [or_info['azimuth']] dips = len(decs) * [or_info['dip']] # if azimuth/dip is missing, plot using specimen coordinates instead else: azimuths, dips = [], [] if any([cb.is_null(az) for az in azimuths if az != 0]): coord = '-1' print("-W- Couldn't find azimuth and dip for {}".format( this_specimen)) print(" Plotting with specimen coordinates instead") elif any([cb.is_null(dip) for dip in dips if dip != 0]): coord = '-1' print("-W- Couldn't find azimuth and dip for {}".format( this_specimen)) print(" Plotting with specimen coordinates instead") else: coord = saved_coord # if azimuth and dip were found, continue with geographic coordinates if coord != "-1" and len(azimuths) > 0: dirs = [decs, incs, azimuths, dips] # this transposes the columns and rows of the list of lists dirs_geo = np.array(list(map(list, list(zip(*dirs))))) decs, incs = pmag.dogeo_V(dirs_geo) if coord == '100' and 'bed_dip_direction' in or_info.keys( ) and or_info[ 'bed_dip_direction'] != "": # need to do tilt correction too bed_dip_dirs = len(decs) * [ or_info['bed_dip_direction'] ] bed_dips = len(decs) * [or_info['bed_dip']] #bed_dip_dirs = pd.to_numeric( # this_specimen_measurements.bed_dip_direction).tolist() # get the azimuths #bed_dips = pd.to_numeric( # this_specimen_measurements.bed_dip).tolist() # get the azimuths dirs = [decs, incs, bed_dip_dirs, bed_dips] ## this transposes the columns and rows of the list of lists dirs_tilt = np.array(list(map(list, list(zip(*dirs))))) decs, incs = pmag.dotilt_V(dirs_tilt) if pmagplotlib.isServer: title = title + "CO:_t_" else: title = title + '_t' else: if pmagplotlib.isServer: title = title + "CO:_g_" else: title = title + '_g' if angle == "": angle = decs[0] ints = pd.to_numeric(this_specimen_measurements[int_key]).tolist() ZI = this_specimen_measurements.ZI.tolist() flags = this_specimen_measurements.quality.tolist() codes = this_specimen_measurements.instrument_codes.tolist() datalist = [tr, decs, incs, ints, ZI, flags, codes] # this transposes the columns and rows of the list of lists datablock = list(map(list, list(zip(*datalist)))) pmagplotlib.plot_zed(ZED, datablock, angle, title, units) if verbose and not set_env.IS_WIN: pmagplotlib.draw_figs(ZED) # # collect info for current_specimen_interpretation dictionary # # # find prior interpretation # prior_specimen_interpretations = [] if len(prior_spec_data): prior_specimen_interpretations = prior_spec_data[ prior_spec_data['specimen'].str.contains( this_specimen) == True] if (beg_pca == "") and (len(prior_specimen_interpretations) != 0): if len(prior_specimen_interpretations) > 0: beg_pcas = pd.to_numeric(prior_specimen_interpretations. meas_step_min.values).tolist() end_pcas = pd.to_numeric(prior_specimen_interpretations. meas_step_max.values).tolist() spec_methods = prior_specimen_interpretations.method_codes.tolist( ) # step through all prior interpretations and plot them for ind in range(len(beg_pcas)): spec_meths = spec_methods[ind].split(':') for m in spec_meths: if 'DE-BFL' in m: calculation_type = 'DE-BFL' # best fit line if 'DE-BFP' in m: calculation_type = 'DE-BFP' # best fit plane if 'DE-FM' in m: calculation_type = 'DE-FM' # fisher mean if 'DE-BFL-A' in m: calculation_type = 'DE-BFL-A' # anchored best fit line if len(beg_pcas) != 0: try: # getting the starting and ending points start, end = tr.index(beg_pcas[ind]), tr.index( end_pcas[ind]) mpars = pmag.domean(datablock, start, end, calculation_type) except ValueError: print( '-W- Specimen record contains invalid start/stop bounds:' ) mpars['specimen_direction_type'] = "Error" # calculate direction/plane if mpars["specimen_direction_type"] != "Error": # put it on the plot pmagplotlib.plot_dir(ZED, mpars, datablock, angle) if verbose and not set_env.IS_WIN: pmagplotlib.draw_figs(ZED) ### SKIP if no prior interpretation - this section should not be used: # else: # try: # start, end = int(beg_pca), int(end_pca) # except ValueError: # beg_pca = 0 # end_pca = len(datablock) - 1 # start, end = int(beg_pca), int(end_pca) # # # calculate direction/plane # try: # mpars = pmag.domean(datablock, start, end, calculation_type) # except Exception as ex: # print('-I- Problem with {}'.format(this_specimen)) # print(' ', ex) # print(' Skipping') # continue # k += 1 # if mpars["specimen_direction_type"] != "Error": # # put it on the plot # pmagplotlib.plot_dir(ZED, mpars, datablock, angle) # if verbose: # pmagplotlib.draw_figs(ZED) if plots == 1 or specimen != "": if plot_file == "": basename = title else: basename = plot_file files = {} for key in list(ZED.keys()): files[key] = basename + '_' + key + '.' + fmt if pmagplotlib.isServer: files[key] = basename + "TY:_{}_.".format(key) + fmt pmagplotlib.save_plots(ZED, files) if specimen != "": sys.exit() if verbose: recnum = 0 for plotrec in datablock: if units == 'T': print('%s: %i %7.1f %s %8.3e %7.1f %7.1f %s' % (plotrec[5], recnum, plotrec[0] * 1e3, " mT", plotrec[3], plotrec[1], plotrec[2], plotrec[6])) if units == "K": print('%s: %i %7.1f %s %8.3e %7.1f %7.1f %s' % (plotrec[5], recnum, plotrec[0] - 273, ' C', plotrec[3], plotrec[1], plotrec[2], plotrec[6])) if units == "J": print('%s: %i %7.1f %s %8.3e %7.1f %7.1f %s' % (plotrec[5], recnum, plotrec[0], ' J', plotrec[3], plotrec[1], plotrec[2], plotrec[6])) if 'K' in units and 'T' in units: if plotrec[0] >= 1.: print('%s: %i %7.1f %s %8.3e %7.1f %7.1f %s' % (plotrec[5], recnum, plotrec[0] - 273, ' C', plotrec[3], plotrec[1], plotrec[2], plotrec[6])) if plotrec[0] < 1.: print('%s: %i %7.1f %s %8.3e %7.1f %7.1f %s' % (plotrec[5], recnum, plotrec[0] * 1e3, " mT", plotrec[3], plotrec[1], plotrec[2], plotrec[6])) recnum += 1 # we have a current interpretation elif mpars["specimen_direction_type"] != "Error": # # create a new specimen record for the interpreation for this # specimen this_specimen_interpretation = { col: "" for col in specimen_cols } # this_specimen_interpretation["analysts"]=user this_specimen_interpretation['software_packages'] = version_num this_specimen_interpretation['specimen'] = this_specimen this_specimen_interpretation["method_codes"] = calculation_type this_specimen_interpretation["meas_step_unit"] = units this_specimen_interpretation["meas_step_min"] = tr[start] this_specimen_interpretation["meas_step_max"] = tr[end] this_specimen_interpretation["dir_dec"] = '%7.1f' % ( mpars['specimen_dec']) this_specimen_interpretation["dir_inc"] = '%7.1f' % ( mpars['specimen_inc']) this_specimen_interpretation["dir_dang"] = '%7.1f' % ( mpars['specimen_dang']) this_specimen_interpretation["dir_n_measurements"] = '%i' % ( mpars['specimen_n']) this_specimen_interpretation["dir_tilt_correction"] = coord methods = methods.replace(" ", "") if "T" in units: methods = methods + ":LP-DIR-AF" if "K" in units: methods = methods + ":LP-DIR-T" if "J" in units: methods = methods + ":LP-DIR-M" this_specimen_interpretation["method_codes"] = methods.strip( ':') this_specimen_interpretation[ "experiments"] = this_specimen_measurements.experiment.unique( )[0] # # print some stuff # if calculation_type != 'DE-FM': this_specimen_interpretation["dir_mad_free"] = '%7.1f' % ( mpars['specimen_mad']) this_specimen_interpretation["dir_alpha95"] = '' if verbose: if units == 'K': print( '%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %7.1f %s \n' % (this_specimen_interpretation["specimen"], int(this_specimen_interpretation[ "dir_n_measurements"]), float(this_specimen_interpretation[ "dir_mad_free"]), float( this_specimen_interpretation["dir_dang"]), float(this_specimen_interpretation[ "meas_step_min"]) - 273, float(this_specimen_interpretation[ "meas_step_max"]) - 273, float( this_specimen_interpretation["dir_dec"]), float( this_specimen_interpretation["dir_inc"]), calculation_type)) elif units == 'T': print( '%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %7.1f %s \n' % (this_specimen_interpretation["specimen"], int(this_specimen_interpretation[ "dir_n_measurements"]), float(this_specimen_interpretation[ "dir_mad_free"]), float( this_specimen_interpretation["dir_dang"]), float(this_specimen_interpretation[ "meas_step_min"]) * 1e3, float(this_specimen_interpretation[ "meas_step_max"]) * 1e3, float( this_specimen_interpretation["dir_dec"]), float( this_specimen_interpretation["dir_inc"]), calculation_type)) elif 'T' in units and 'K' in units: if float(this_specimen_interpretation[ 'meas_step_min']) < 1.0: min = float(this_specimen_interpretation[ 'meas_step_min']) * 1e3 else: min = float(this_specimen_interpretation[ 'meas_step_min']) - 273 if float(this_specimen_interpretation[ 'meas_step_max']) < 1.0: max = float(this_specimen_interpretation[ 'meas_step_max']) * 1e3 else: max = float(this_specimen_interpretation[ 'meas_step_max']) - 273 print( '%s %i %7.1f %i %i %7.1f %7.1f %7.1f %s \n' % (this_specimen_interpretation["specimen"], int(this_specimen_interpretation[ "dir_n_measurements"]), float(this_specimen_interpretation[ "dir_mad_free"]), float( this_specimen_interpretation["dir_dang"]), min, max, float( this_specimen_interpretation["dir_dec"]), float( this_specimen_interpretation["dir_inc"]), calculation_type)) else: print( '%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %7.1f %s \n' % (this_specimen_interpretation["specimen"], int(this_specimen_interpretation[ "dir_n_measurements"]), float(this_specimen_interpretation[ "dir_mad_free"]), float( this_specimen_interpretation["dir_dang"]), float(this_specimen_interpretation[ "meas_step_min"]), float(this_specimen_interpretation[ "meas_step_max"]), float( this_specimen_interpretation["dir_dec"]), float( this_specimen_interpretation["dir_inc"]), calculation_type)) else: this_specimen_interpretation["dir_alpha95"] = '%7.1f' % ( mpars['specimen_alpha95']) this_specimen_interpretation["dir_mad_free"] = '' if verbose: if 'K' in units: print( '%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %7.1f %s \n' % (this_specimen_interpretation["specimen"], int(this_specimen_interpretation[ "dir_n_measurments"]), float(this_specimen_interpretation[ "dir_mad_free"]), float( this_specimen_interpretation["dir_dang"]), float(this_specimen_interpretation[ "meas_step_min"]) - 273, float(this_specimen_interpretation[ "meas_step_max"]) - 273, float( this_specimen_interpretation["dir_dec"]), float( this_specimen_interpretation["dir_inc"]), calculation_type)) elif 'T' in units: print( '%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %7.1f %s \n' % (this_specimen_interpretation["specimen"], int(this_specimen_interpretation[ "dir_n_measurements"]), float(this_specimen_interpretation[ "dir_alpha95"]), float( this_specimen_interpretation["dir_dang"]), float(this_specimen_interpretation[ "meas_step_min"]) * 1e3, float(this_specimen_interpretation[ "meas_step_max"]) * 1e3, float( this_specimen_interpretation["dir_dec"]), float( this_specimen_interpretation["dir_inc"]), calculation_type)) elif 'T' in units and 'K' in units: if float(this_specimen_interpretation[ 'meas_step_min']) < 1.0: min = float(this_specimen_interpretation[ 'meas_step_min']) * 1e3 else: min = float(this_specimen_interpretation[ 'meas_step_min']) - 273 if float(this_specimen_interpretation[ 'meas_step_max']) < 1.0: max = float(this_specimen_interpretation[ 'meas_step_max']) * 1e3 else: max = float(this_specimen_interpretation[ 'meas_step_max']) - 273 print('%s %i %7.1f %i %i %7.1f %7.1f %s \n' % ( this_specimen_interpretation["specimen"], int(this_specimen_interpretation[ "dir_n_measurements"]), float( this_specimen_interpretation["dir_alpha95"] ), min, max, float(this_specimen_interpretation["dir_dec"]), float(this_specimen_interpretation["dir_inc"]), calculation_type)) else: print( '%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %s \n' % (this_specimen_interpretation["specimen"], int(this_specimen_interpretation[ "dir_n_measurements"]), float(this_specimen_interpretation[ "dir_alpha95"]), float(this_specimen_interpretation[ "meas_step_min"]), float(this_specimen_interpretation[ "meas_step_max"]), float( this_specimen_interpretation["dir_dec"]), float( this_specimen_interpretation["dir_inc"]), calculation_type)) if verbose: saveit = input("Save this interpretation? [y]/n \n") else: print("no data", this_specimen) if verbose: pmagplotlib.draw_figs(ZED) #res = input(' <return> for next specimen, [q]uit ') res = input("S[a]ve plots, [q]uit, or <return> to continue ") if res == 'a': files = { plot_type: this_specimen + "_" + plot_type + "." + fmt for plot_type in ZED } pmagplotlib.save_plots(ZED, files) print("") if res == 'q': return k += 1
def main(): """ NAME make_magic_plots.py DESCRIPTION inspects magic directory for available data and makes plots SYNTAX make_magic_plots.py [command line options] INPUT magic files OPTIONS -h prints help message and quits -f FILE specifies input file name -fmt [png,eps,svg,jpg,pdf] specify format, default is png """ if '-h' in sys.argv: print(main.__doc__) sys.exit() # reset log files for fname in ['log.txt', 'errors.txt']: f = os.path.join(os.getcwd(), fname) if os.path.exists(f): os.remove(f) dirlist = ['./'] dir_path = os.getcwd() # if '-fmt' in sys.argv: ind = sys.argv.index("-fmt") fmt = sys.argv[ind + 1] else: fmt = 'png' if '-f' in sys.argv: ind = sys.argv.index("-f") filelist = [sys.argv[ind + 1]] else: filelist = os.listdir(dir_path) ## initialize some variables samp_file = 'samples.txt' azimuth_key = 'azimuth' meas_file = 'measurements.txt' loc_key = 'location' loc_file = 'locations.txt' method_key = 'method_codes' dec_key = 'dir_dec' inc_key = 'dir_inc' tilt_corr_key = "dir_tilt_correction" aniso_tilt_corr_key = "aniso_tilt_correction" hyst_bcr_key = "hyst_bcr" hyst_mr_key = "hyst_mr_moment" hyst_ms_key = "hyst_ms_moment" hyst_bc_key = "hyst_bc" Mkeys = ['magnitude', 'magn_moment', 'magn_volume', 'magn_mass'] results_file = 'sites.txt' hyst_file = 'specimens.txt' aniso_file = 'specimens.txt' # create contribution and propagate data throughout con = cb.Contribution() con.propagate_location_to_measurements() con.propagate_location_to_specimens() con.propagate_location_to_samples() if not con.tables: print('-E- No MagIC tables could be found in this directory') error_log("No MagIC tables found") return # try to get the contribution id for error logging con_id = "" if 'contribution' in con.tables: if 'id' in con.tables['contribution'].df.columns: con_id = con.tables['contribution'].df.iloc[0]['id'] # check to see if propagation worked, otherwise you can't plot by location lowest_table = None for table in con.ancestry: if table in con.tables: lowest_table = table break do_full_directory = False # check that locations propagated down to the lowest table in the contribution if 'location' in con.tables[lowest_table].df.columns: if 'locations' not in con.tables: info_log('location names propagated to {}, but could not be validated'.format(lowest_table)) # are there any locations in the lowest table? elif not all(con.tables[lowest_table].df['location'].isnull()): locs = con.tables['locations'].df.index.unique() lowest_locs = con.tables[lowest_table].df['location'].unique() incorrect_locs = set(lowest_locs).difference(set(locs)) # are they actual locations? if not incorrect_locs: info_log('location names propagated to {}'.format(lowest_table)) else: do_full_directory = True error_log('location names did not propagate fully to {} table (looks like there are some naming inconsistencies between tables)'.format(lowest_table), con_id=con_id) else: do_full_directory = True error_log('could not propagate location names down to {} table'.format(lowest_table), con_id=con_id) else: do_full_directory = True error_log('could not propagate location names down to {} table'.format(lowest_table), con_id=con_id) all_data = {} all_data['measurements'] = con.tables.get('measurements', None) all_data['specimens'] = con.tables.get('specimens', None) all_data['samples'] = con.tables.get('samples', None) all_data['sites'] = con.tables.get('sites', None) all_data['locations'] = con.tables.get('locations', None) if 'locations' in con.tables: locations = con.tables['locations'].df.index.unique() else: locations = [''] dirlist = [loc for loc in locations if cb.not_null(loc, False) and loc != 'nan'] if not dirlist: dirlist = ["./"] if do_full_directory: dirlist = ["./"] # plot the whole contribution as one location if dirlist == ["./"]: error_log('plotting the entire contribution as one location', con_id=con_id) for fname in os.listdir("."): if fname.endswith(".txt"): shutil.copy(fname, "tmp_" + fname) # if possible, go through all data by location # use tmp_*.txt files to separate out by location for loc in dirlist: print('\nworking on: ', loc) def get_data(dtype, loc_name): """ Extract data of type dtype for location loc_name. Write tmp_dtype.txt files if possible. """ if cb.not_null(all_data[dtype], False): data_container = all_data[dtype] if loc_name == "./": data_df = data_container.df else: # awkward workaround for chars like "(" and "?" that break in regex try: data_df = data_container.df[data_container.df['location'].astype(str).str.contains(loc_name, na=False)] except: #sre_constants.error: data_df = data_container.df[data_container.df['location'] == loc_name] data = data_container.convert_to_pmag_data_list(df=data_df) res = data_container.write_magic_file('tmp_{}.txt'.format(dtype), df=data_df) if not res: return [] return data meas_data = get_data('measurements', loc) spec_data = get_data('specimens', loc) samp_data = get_data('samples', loc) site_data = get_data('sites', loc) loc_data = get_data('locations', loc) if loc == "./": # if you can't sort by location, do everything together try: meas_data = con.tables['measurements'].convert_to_pmag_data_list() except KeyError: meas_data = None try: spec_data = con.tables['specimens'].convert_to_pmag_data_list() except KeyError: spec_data = None try: samp_data = con.tables['samples'].convert_to_pmag_data_list() except KeyError: samp_data = None try: site_data = con.tables['sites'].convert_to_pmag_data_list() except KeyError: site_data = None crd = 's' if samp_file in filelist and samp_data: # find coordinate systems samps = samp_data file_type = "samples" # get all non blank sample orientations Srecs = pmag.get_dictitem(samps, azimuth_key, '', 'F') if len(Srecs) > 0: crd = 'g' print('using geographic coordinates') else: print('using specimen coordinates') else: if VERBOSE: print('-I- No sample data found') if meas_file in filelist and meas_data: # start with measurement data print('working on measurements data') data = meas_data file_type = 'measurements' # looking for zeq_magic possibilities # get all non blank method codes AFZrecs = pmag.get_dictitem(data, method_key, 'LT-AF-Z', 'has') # get all non blank method codes TZrecs = pmag.get_dictitem(data, method_key, 'LT-T-Z', 'has') # get all non blank method codes MZrecs = pmag.get_dictitem(data, method_key, 'LT-M-Z', 'has') # get all dec measurements Drecs = pmag.get_dictitem(data, dec_key, '', 'F') # get all inc measurements Irecs = pmag.get_dictitem(data, inc_key, '', 'F') for key in Mkeys: Mrecs = pmag.get_dictitem( data, key, '', 'F') # get intensity data if len(Mrecs) > 0: break # potential for stepwise demag curves if len(AFZrecs) > 0 or len(TZrecs) > 0 or len(MZrecs) > 0 and len(Drecs) > 0 and len(Irecs) > 0 and len(Mrecs) > 0: CMD = 'zeq_magic.py -f tmp_measurements.txt -fsp tmp_specimens.txt -fsa tmp_samples.txt -fsi tmp_sites.txt -sav -fmt ' + fmt + ' -crd ' + crd + " -new" print(CMD) info_log(CMD, loc) os.system(CMD) # looking for thellier_magic possibilities if len(pmag.get_dictitem(data, method_key, 'LP-PI-TRM', 'has')) > 0: CMD = 'thellier_magic.py -f tmp_measurements.txt -fsp tmp_specimens.txt -sav -fmt ' + fmt print(CMD) info_log(CMD, loc) os.system(CMD) # looking for hysteresis possibilities if len(pmag.get_dictitem(data, method_key, 'LP-HYS', 'has')) > 0: # find hyst experiments # check for reqd columns missing = check_for_reqd_cols(data, ['treat_temp']) if missing: error_log('LP-HYS method code present, but required column(s) [{}] missing'.format(", ".join(missing)), loc, "quick_hyst.py", con_id=con_id) else: CMD = 'quick_hyst.py -f tmp_measurements.txt -sav -fmt ' + fmt print(CMD) info_log(CMD, loc) os.system(CMD) # equal area plots of directional data # at measurment level (by specimen) if data: missing = check_for_reqd_cols(data, ['dir_dec', 'dir_inc']) if not missing: CMD = "eqarea_magic.py -f tmp_measurements.txt -obj spc -sav -no-tilt -fmt " + fmt print(CMD) os.system(CMD) info_log(CMD, loc, "eqarea_magic.py") else: if VERBOSE: print('-I- No measurement data found') # site data if results_file in filelist and site_data: print('-I- result file found', results_file) data = site_data file_type = 'sites' print('-I- working on site directions') print('number of datapoints: ', len(data), loc) dec_key = 'dir_dec' inc_key = 'dir_inc' int_key = 'int_abs' SiteDIs = pmag.get_dictitem(data, dec_key, "", 'F') # find decs SiteDIs = pmag.get_dictitem( SiteDIs, inc_key, "", 'F') # find decs and incs dir_data_found = len(SiteDIs) print('{} Dec/inc pairs found'.format(dir_data_found)) if SiteDIs: # then convert tilt_corr_key to correct format old_SiteDIs = SiteDIs SiteDIs = [] for rec in old_SiteDIs: if tilt_corr_key not in rec: rec[tilt_corr_key] = "0" # make sure tilt_corr_key is a correct format try: rec[tilt_corr_key] = str(int(float(rec[tilt_corr_key]))) except ValueError: rec[tilt_corr_key] = "0" SiteDIs.append(rec) print('number of individual directions: ', len(SiteDIs)) # tilt corrected coordinates SiteDIs_t = pmag.get_dictitem(SiteDIs, tilt_corr_key, '100', 'T', float_to_int=True) print('number of tilt corrected directions: ', len(SiteDIs_t)) SiteDIs_g = pmag.get_dictitem( SiteDIs, tilt_corr_key, '0', 'T', float_to_int=True) # geographic coordinates print('number of geographic directions: ', len(SiteDIs_g)) SiteDIs_s = pmag.get_dictitem( SiteDIs, tilt_corr_key, '-1', 'T', float_to_int=True) # sample coordinates print('number of sample directions: ', len(SiteDIs_s)) SiteDIs_x = pmag.get_dictitem( SiteDIs, tilt_corr_key, '', 'T') # no coordinates print('number of no coordinates directions: ', len(SiteDIs_x)) if len(SiteDIs_t) > 0 or len(SiteDIs_g) > 0 or len(SiteDIs_s) > 0 or len(SiteDIs_x) > 0: CRD = "" if len(SiteDIs_t) > 0: CRD = ' -crd t' elif len(SiteDIs_g) > 0: CRD = ' -crd g' elif len(SiteDIs_s) > 0: CRD = ' -crd s' CMD = 'eqarea_magic.py -f tmp_sites.txt -fsp tmp_specimens.txt -fsa tmp_samples.txt -flo tmp_locations.txt -sav -fmt ' + fmt + CRD print(CMD) info_log(CMD, loc) os.system(CMD) else: if dir_data_found: error_log('{} dec/inc pairs found, but no equal area plots were made'.format(dir_data_found), loc, "equarea_magic.py", con_id=con_id) # print('-I- working on VGP map') VGPs = pmag.get_dictitem( SiteDIs, 'vgp_lat', "", 'F') # are there any VGPs? if len(VGPs) > 0: # YES! CMD = 'vgpmap_magic.py -f tmp_sites.txt -prj moll -res c -sym ro 5 -sav -fmt png' print(CMD) info_log(CMD, loc, 'vgpmap_magic.py') os.system(CMD) else: print('-I- No vgps found') print('-I- Look for intensities') # is there any intensity data? if site_data: if int_key in site_data[0].keys(): # old way, wasn't working right: #CMD = 'magic_select.py -key ' + int_key + ' 0. has -F tmp1.txt -f tmp_sites.txt' Selection = pmag.get_dictkey(site_data, int_key, dtype="f") with open('intensities.txt', 'w') as out: for rec in Selection: if rec != 0: out.write(str(rec * 1e6) + "\n") loc = loc.replace(" ", "_") if loc == "./": loc_name = "" else: loc_name = loc histfile = 'LO:_' + loc_name + \ '_TY:_intensities_histogram:_.' + fmt # maybe run histplot.main here instead, so you can return an error message CMD = "histplot.py -twin -b 1 -xlab 'Intensity (uT)' -sav -f intensities.txt -F " + histfile os.system(CMD) info_log(CMD, loc) print(CMD) else: print('-I- No intensities found') else: print('-I- No intensities found') ## if hyst_file in filelist and spec_data: print('working on hysteresis', hyst_file) data = spec_data file_type = 'specimens' hdata = pmag.get_dictitem(data, hyst_bcr_key, '', 'F') hdata = pmag.get_dictitem(hdata, hyst_mr_key, '', 'F') hdata = pmag.get_dictitem(hdata, hyst_ms_key, '', 'F') # there are data for a dayplot hdata = pmag.get_dictitem(hdata, hyst_bc_key, '', 'F') if len(hdata) > 0: CMD = 'dayplot_magic.py -f tmp_specimens.txt -sav -fmt ' + fmt info_log(CMD, loc) print(CMD) else: print('no hysteresis data found') if aniso_file in filelist and spec_data: # do anisotropy plots if possible print('working on anisotropy', aniso_file) data = spec_data file_type = 'specimens' # make sure there is some anisotropy data if not data: print('No anisotropy data found') elif 'aniso_s' not in data[0]: print('No anisotropy data found') else: # get specimen coordinates if aniso_tilt_corr_key not in data[0]: sdata = data else: sdata = pmag.get_dictitem( data, aniso_tilt_corr_key, '-1', 'T', float_to_int=True) # get specimen coordinates gdata = pmag.get_dictitem( data, aniso_tilt_corr_key, '0', 'T', float_to_int=True) # get specimen coordinates tdata = pmag.get_dictitem( data, aniso_tilt_corr_key, '100', 'T', float_to_int=True) CRD = "" CMD = 'aniso_magic.py -x -B -sav -fmt ' + fmt + " -new" if len(sdata) > 3: CMD = CMD + ' -crd s' print(CMD) info_log(CMD, loc) os.system(CMD) if len(gdata) > 3: CMD = CMD + ' -crd g' print(CMD) info_log(CMD, loc) os.system(CMD) if len(tdata) > 3: CMD = CMD + ' -crd t' print(CMD) info_log(CMD, loc) os.system(CMD) # remove temporary files for fname in glob.glob('tmp*.txt'): os.remove(fname) try: os.remove('intensities.txt') except FileNotFoundError: pass if loc_file in filelist and loc_data: #data, file_type = pmag.magic_read(loc_file) # read in location data data = loc_data print('-I- working on pole map') poles = pmag.get_dictitem( data, 'pole_lat', "", 'F') # are there any poles? poles = pmag.get_dictitem( poles, 'pole_lon', "", 'F') # are there any poles? if len(poles) > 0: # YES! CMD = 'polemap_magic.py -sav -fmt png -rev gv 40' print(CMD) info_log(CMD, "all locations", "polemap_magic.py") os.system(CMD) else: print('-I- No poles found') thumbnails.make_thumbnails(dir_path)