from __future__ import with_statement import sys try: import numpy import re import reflex from pipeline_product import PipelineProduct import pipeline_display import reflex_plot_widgets import matplotlib.gridspec as gridspec import_success = True except ImportError: import_success = False print "Error importing modules pyfits, wx, matplotlib, numpy" def paragraph(text, width=None): """ wrap text string into paragraph text: text to format, removes leading space and newlines width: if not None, wraps text, not recommended for tooltips as they are wrapped by wxWidgets by default """ import textwrap if width is None: return textwrap.dedent(text).replace('\n', ' ').strip() else: return textwrap.fill(textwrap.dedent(text), width=width) class DataPlotterManager(object): # static members recipe_name = "kmos_std_star" star_spec_cat = "STAR_SPEC" telluric_cat = "TELLURIC" std_image_cat = "STD_IMAGE" y_scalefactor = 1000 def setWindowTitle(self): return self.recipe_name+"_interactive" def setInteractiveParameters(self): return [ reflex.RecipeParameter(recipe=self.recipe_name, displayName="imethod", group="Recons.", description="Interpolation Method (NN, lwNN, swNN, MS, CS)"), reflex.RecipeParameter(recipe=self.recipe_name, displayName="xcal_interpolation", group="Recons.", description="Interpolate xcal between rotator angles"), reflex.RecipeParameter(recipe=self.recipe_name, displayName="mask_method", group="Extr.", description="Extraction Method (optimal/integrated)"), reflex.RecipeParameter(recipe=self.recipe_name, displayName="centre", group="Extr.", description="Centre (integrated only)"), reflex.RecipeParameter(recipe=self.recipe_name, displayName="radius", group="Extr.", description="Radius (integrated only)"), reflex.RecipeParameter(recipe=self.recipe_name, displayName="fmethod", group="Extr.", description="Fitting Method (gauss, moffat)"), reflex.RecipeParameter(recipe=self.recipe_name, displayName="neighborhoodRange", group="Extr.", description="Range for Neighbors"), reflex.RecipeParameter(recipe=self.recipe_name, displayName="flux", group="Extr.", description="Apply flux conservation"), reflex.RecipeParameter(recipe=self.recipe_name, displayName="cmethod", group="Comb.", description="Combination Method (average, median, sum, min_max, ksigma)"), reflex.RecipeParameter(recipe=self.recipe_name, displayName="cpos_rej", group="Comb.", description="The positive rejection threshold"), reflex.RecipeParameter(recipe=self.recipe_name, displayName="cneg_rej", group="Comb.", description="The negative rejection threshold"), reflex.RecipeParameter(recipe=self.recipe_name, displayName="citer", group="Comb.", description="The number of iterations"), reflex.RecipeParameter(recipe=self.recipe_name, displayName="cmax", group="Comb.", description="The number of maximum pixel values"), reflex.RecipeParameter(recipe=self.recipe_name, displayName="cmin", group="Comb.", description="The number of minimum pixel values"), reflex.RecipeParameter(recipe=self.recipe_name, displayName="startype", group="Star", description="The star spectral type (O, B, A, F, G)"), reflex.RecipeParameter(recipe=self.recipe_name, displayName="magnitude", group="Star", description="Star Magnitude"), ] def readFitsData(self, fitsFiles): self.frames = dict() for f in fitsFiles: self.frames[f.category] = PipelineProduct(f) # Two cases: the file category is found or not found. # Define the plotting functions in both cases if self.std_image_cat in self.frames and self.star_spec_cat in self.frames and self.telluric_cat in self.frames: # Get the wished files std_image = self.frames[self.std_image_cat] star_spec = self.frames[self.star_spec_cat] telluric = self.frames[self.telluric_cat] # Initialise self.star_data_extnames = [] self.qc_std_trace = dict() self.qc_spat_res = dict() self.image_std = dict() self.image_std_avg = dict() self.image_std_stdev = dict() self.qc_thruput = dict() self.qc_zpoint = dict() self.crpix1 = dict() self.crval1 = dict() self.cdelt1 = dict() self.spec_data = dict() self.spec_noise = dict() # READ data self.qc_nr_std_stars = star_spec.all_hdu[0].header['ESO QC NR STD STARS'] self.qc_thruput_mean = star_spec.all_hdu[0].header['ESO QC THRUPUT MEAN'] self.qc_thruput_sdv = star_spec.all_hdu[0].header['ESO QC THRUPUT SDV'] # Loop on all extensions of std_image to find the std stars extensions for std_image_ext in std_image.all_hdu: naxis = std_image_ext.header['NAXIS'] # NAXIS is 2 if there is an image, 0 otherwise if (naxis == 2): # extname is like IFU.3.DATA extname = std_image_ext.header['EXTNAME'] self.star_data_extnames.append(extname) self.qc_std_trace[extname] = std_image_ext.header['ESO QC STD TRACE'] self.qc_spat_res[extname] = std_image_ext.header['ESO QC SPAT RES'] self.image_std[extname] = std_image_ext.data self.image_std_avg[extname] = numpy.average(std_image_ext.data) self.image_std_stdev[extname] = numpy.std(std_image_ext.data) # Get infos from star_spec using the extname self.qc_thruput[extname] = star_spec.all_hdu[extname].header['ESO QC THRUPUT'] self.qc_zpoint[extname] = star_spec.all_hdu[extname].header['ESO QC ZPOINT'] self.crpix1[extname] = star_spec.all_hdu[extname].header['CRPIX1'] self.crval1[extname] = star_spec.all_hdu[extname].header['CRVAL1'] self.cdelt1[extname] = star_spec.all_hdu[extname].header['CDELT1'] self.spec_data[extname] = star_spec.all_hdu[extname].data # noise_extname is like IFU.3.NOISE noise_extname = re.sub("DATA", "NOISE", extname) self.spec_noise[extname] = star_spec.all_hdu[noise_extname].data # Set the plotting functions self._add_subplots = self._add_subplots self._plot = self._data_plot else: # Set the plotting functions to NODATA ones self._add_subplots = self._add_nodata_subplots self._plot = self._nodata_plot def addSubplots(self, figure): self._add_subplots(figure) def plotProductsGraphics(self): self._plot() def plotWidgets(self) : widgets = list() # Radio button self.radiobutton = reflex_plot_widgets.InteractiveRadioButtons(self.axradiobutton, self.setRadioCallback, self.star_data_extnames, 0, title='Standard star selection') widgets.append(self.radiobutton) return widgets def setRadioCallback(self, label) : # Setup the image display imgdisp = pipeline_display.ImageDisplay() imgdisp.setAspect('equal') imgdisp.z_lim = (self.image_std_avg[label] - self.image_std_stdev[label], self.image_std_avg[label] + 2 * self.image_std_stdev[label]) imgdisp.display(self.img_plot, "Median collapsed cube (STD_IMAGE)\nFWHM "+ r"$\simeq$ " +str( numpy.round(self.qc_spat_res[label], 2) )+ " [arcsec]", self._data_plot_get_tooltip(label), self.image_std[label]) self.img_plot.set_xlabel("pixels") self.img_plot.set_ylabel("pixels") # Define wave pix = numpy.arange(len(self.spec_data[label])) wave = self.crval1[label] + pix * self.cdelt1[label] # Plot Spectrum specdisp = pipeline_display.SpectrumDisplay() self.spec_plot.clear() specdisp.setLabels(r"$\lambda$["+"$\mu$m]", "Flux (ADU) [x"+str(self.y_scalefactor)+"]" ) specdisp.display(self.spec_plot, "Extracted Standard Star Spectrum (STAR_SPEC)", self._data_plot_get_tooltip(label), wave, self.spec_data[label]/self.y_scalefactor) # TO DO: Unify plotting in one function. if (self.spec_noise[label] is not None): # Overplot the Noise spectrum specdisp.overplot(self.spec_plot, wave, self.spec_noise[label]/self.y_scalefactor, 'red') # TO DO: Unify plotting in one function. self.spec_plot.legend(('Flux', 'Noise')) def _add_subplots(self, figure): gs = gridspec.GridSpec(2, 2) self.axradiobutton = figure.add_subplot(gs[0,0]) self.img_plot = figure.add_subplot(gs[0,1]) self.spec_plot = figure.add_subplot(gs[1,:]) def _data_plot_get_tooltip(self, extname): # Create the tooltip tooltip = " \ ESO QC NR STD STARS : %f \n \ ESO QC THRUPUT MEAN : %f \n \ ESO QC THRUPUT SDV : %f \n \ ESO QC STD TRACE : %f \n \ ESO QC SPAT RES : %f \n \ ESO QC THRUPUT : %f \n \ ESO QC ZPOINT : %f \ " % (self.qc_nr_std_stars, self.qc_thruput_mean, self.qc_thruput_sdv, self.qc_std_trace[extname], self.qc_spat_res[extname], self.qc_thruput[extname], self.qc_zpoint[extname]) return tooltip def _data_plot(self): extname = self.star_data_extnames[0] imgdisp = pipeline_display.ImageDisplay() imgdisp.setAspect('equal') imgdisp.z_lim = (self.image_std_avg[extname] - self.image_std_stdev[extname], self.image_std_avg[extname] + 2 * self.image_std_stdev[extname]) imgdisp.display(self.img_plot, "Median collapsed cube (STD_IMAGE)\nFWHM "+ r"$\simeq$ " +str( numpy.round(self.qc_spat_res[extname], 2) )+ " [arcsec]", self._data_plot_get_tooltip(extname), self.image_std[extname]) #Please alert if it shuld be latex "\approx" instead of "\simeq". self.img_plot.set_xlabel("pixels") self.img_plot.set_ylabel("pixels") # Define wave pix = numpy.arange(len(self.spec_data[extname])) wave = self.crval1[extname] + pix * self.cdelt1[extname] # Plot Spectrum specdisp = pipeline_display.SpectrumDisplay() specdisp.setLabels(r"$\lambda$["+"$\mu$m]", "Flux (ADU) [x"+str(self.y_scalefactor)+"]" ) specdisp.display(self.spec_plot, "Extracted Standard Star Spectrum (STAR_SPEC)", self._data_plot_get_tooltip(extname), wave, self.spec_data[extname]/self.y_scalefactor) # TO DO: Unify plotting in one function. if (self.spec_noise[extname] is not None): # Overplot the Noise spectrum specdisp.overplot(self.spec_plot, wave, self.spec_noise[extname]/self.y_scalefactor, 'red') # TO DO: Unify plotting in one function. self.spec_plot.legend(('Flux', 'Noise')) def _add_nodata_subplots(self, figure): self.img_plot = figure.add_subplot(1,1,1) def _nodata_plot(self): # could be moved to reflex library? self.img_plot.set_axis_off() text_nodata = "Data not found" self.img_plot.text(0.1, 0.6, text_nodata, color='#11557c', fontsize=18, ha='left', va='center', alpha=1.0) self.img_plot.tooltip = text_nodata #This is the 'main' function if __name__ == '__main__': from reflex_interactive_app import PipelineInteractiveApp # Create interactive application interactive_app = PipelineInteractiveApp(enable_init_sop=True) # get inputs from the command line interactive_app.parse_args() #Check if import failed or not if not import_success: interactive_app.setEnableGUI(False) #Open the interactive window if enabled if interactive_app.isGUIEnabled(): #Get the specific functions for this window dataPlotManager = DataPlotterManager() interactive_app.setPlotManager(dataPlotManager) interactive_app.showGUI() else: interactive_app.set_continue_mode() #Print outputs. This is parsed by the Reflex python actor to #get the results. Do not remove interactive_app.print_outputs() sys.exit()