import matplotlib as mpl # mpl.use('Agg') # necessary to be able to generate the reports even without X server from matplotlib.pylab import plt import numpy as np from .log import Log, ERROR, WARNING, NOTICE log = Log() quantity_lookup = { "VIS2": ("VIS2DATA", "VIS2ERR","vis2"), "VIS2DATA": ("VIS2DATA", "VIS2ERR","vis2"), "T3PHI" : ("T3PHI", "T3PHIERR","oi_t3"), "T3AMP" : ("T3AMP", "T3AMPERR","oi_t3"), "VISAMP": ("VISAMP", "VISAMPERR","vis"), "VISPHI": ("VISPHI", "VISPHIERR","vis") } # # get and format a single data, we can triger specific query and post processing # for "BASELINE", "BASENAME", "SP_FREQ"... but surely more interesting for further # sorting to actually define these column and fill them # def get_data_for_plot(db, tbl, value, tbls="", const="", func=None, flatten=True): if tbl=="flux": str = "SELECT "+value+" from "+tbl+",targets,wavelengths,headers,arrays as ar1"+tbls+" where ar1.[FILEID]="+tbl+".[FILEID] and ar1.STA_INDEX="+tbl+".STA1_INDEX and "+tbl+".[FILEID]=targets.[FILEID] and "+tbl+".[TARGET_ID]=targets.[TARGET_ID] and wavelengths.[FILEID]="+tbl+".[FILEID] and wavelengths.[INSNAME]="+tbl+".[INSNAME] and headers.[FILEID]="+tbl+".[FILEID] "+const elif tbl=="t3": str = "SELECT "+value+" from "+tbl+",targets,wavelengths,headers,arrays as ar1,arrays as ar2,arrays as ar3"+tbls+" where ar1.[FILEID]="+tbl+".[FILEID] and ar1.STA_INDEX="+tbl+".STA1_INDEX and ar2.[FILEID]="+tbl+".[FILEID] and ar2.STA_INDEX="+tbl+".STA2_INDEX and ar3.STA_INDEX="+tbl+".STA3_INDEX and "+tbl+".[FILEID]=targets.[FILEID] and "+tbl+".[TARGET_ID]=targets.[TARGET_ID] and wavelengths.[FILEID]="+tbl+".[FILEID] and wavelengths.[INSNAME]="+tbl+".[INSNAME] and headers.[FILEID]="+tbl+".[FILEID] "+const else: str = "SELECT "+value+" from "+tbl+",targets,wavelengths,headers,arrays as ar1,arrays as ar2"+tbls+" where ar1.[FILEID]="+tbl+".[FILEID] and ar1.STA_INDEX="+tbl+".STA1_INDEX and ar2.[FILEID]="+tbl+".[FILEID] and ar2.STA_INDEX="+tbl+".STA2_INDEX and "+tbl+".[FILEID]=targets.[FILEID] and "+tbl+".[TARGET_ID]=targets.[TARGET_ID] and wavelengths.[FILEID]="+tbl+".[FILEID] and wavelengths.[INSNAME]="+tbl+".[INSNAME] and headers.[FILEID]="+tbl+".[FILEID] "+const data = db.execute(str).fetchall() if flatten is True: data = list(zip( *data ))[0] if func is not None: data = [ func(d) for d in data ] return data # # Very fast routine to plot a scatter of variable # Main drawback: marker cannot be vectorialised. # def plot_couple(db, tbl, x, y, yerr=None, xerr=None, axes=None, xfunc=None,yfunc=None,eyfunc=None,exfunc=None, const="", constx="", consty="", tbls="", **kwargs): xdatas = get_data_for_plot(db, tbl, x, const=const+constx, func=xfunc, tbls=tbls); ydatas = get_data_for_plot(db, tbl, y, const=const+consty, func=yfunc, tbls=tbls); if yerr is not None: eydatas = get_data_for_plot(db, tbl, yerr, const=const+consty, func=eyfunc, tbls=tbls); if xerr is not None: exdatas = get_data_for_plot(db, tbl, xerr, const=const+constx, func=exfunc, tbls=tbls); print(xdatas) print(ydatas) print(exdatas) print(eydatas) # plot error bars if yerr is not None: i,j,k = axes.errorbar(xdatas,ydatas,linestyle="none",yerr=eydatas,c='gray') k[0].set_alpha(0.3) j[0].set_alpha(0.3) j[1].set_alpha(0.3) if yerr is not None and xerr is not None: i,j,k = axes.errorbar(xdatas,ydatas,linestyle="none",yerr=eydatas,xerr=exdatas,c='gray') k[0].set_alpha(0.3) j[0].set_alpha(0.3) j[1].set_alpha(0.3) # plot symbols axes.scatter( xdatas, ydatas, zorder=100, **kwargs ) def make_dictionary(db, values, query, row2key=lambda r:r[0]): """ values can be an iterable or a function with signature (i,N,r) where i is the row index 0,1,2,3 ,....,N ; N the number of row and r is the value of that row """ c = db.execute(query) if hasattr(values, "__call__"): func = values rows = [(row2key(r),r) for r in c] Nkeys = len(rows) return {k:func(i,Nkeys,r) for i,(k,r) in enumerate(rows)} else: N = len(values) return {row2key(r):values[i%N] for i,r in enumerate(c)} def make_target_dictionary(db, values=list("bgrkcy")): query="SELECT DISTiNCT TARGET FROM targets" return make_dictionary(db, values, query, lambda r:r[0]) def make_setup_dictionary(db, values=list("osx21")): query="SELECT DISTiNCT [ESO INS SPEC RES],[ESO INS POLA MODE],[ESO INS TIM2 PERIOD],[ESO DET2 SEQ1 DIT] FROM headers" return make_dictionary(db, values, query, lambda r:tuple(r)) def axes_maker(fig=None, orientation=0,extra=lambda ax,r:None, sharex=False, sharey=False, **kwargs): fig = fig or plt.gcf() if orientation: def make_ax(i,N,r): ax = fig.add_subplot(N, 1,i+1, **kwargs) if not i and sharey: kwargs["sharey"] = ax ax.first_axes = not i ax.last_axes = i==(N-1) extra(ax,r) return ax else: def make_ax(i,N,r): ax = fig.add_subplot(N, i+1,1, **kwargs) if not i and sharex: kwargs["sharex"] = ax ax.first_axes = not i ax.last_axes = i==(N-1) extra(ax,r) return ax return make_ax def _extra_base(ax,r): ax.set_title(r[2]+r[3]) def make_base_dictionary(db, maker=None, tbl="vis2"): """ e.g.: make_base_dictionary(db, axes_maker(fig)) """ if maker is None: maker = axes_maker(extra=_extra_base) query = "SELECT DISTINCT STA1_NAME, STA2_NAME, ar1.STA_NAME, ar2.STA_NAME FROM %s, arrays as ar1, arrays as ar2 WHERE STA1_INDEX = ar1.STA_INDEX AND STA2_INDEX = ar2.STA_INDEX "%tbl return make_dictionary(db, maker, query, lambda r:r[0:2]) def _extra_triplet(ax,r): ax.set_title(r[3]+r[4]+r[5]) def make_triplet_dictionary(db, maker=None, tbl="oi_t3"): """ e.g.: make_triplet_dictionary(db, axes_maker(fig)) """ if maker is None: maker = axes_maker(extra=_extra_triplet) query = "SELECT DISTINCT STA1_INDEX, STA2_INDEX, STA3_INDEX, ar1.STA_NAME, ar2.STA_NAME, ar3.STA_NAME FROM %s, arrays as ar1, arrays as ar2, arrays as ar3 WHERE STA1_INDEX = ar1.STA_INDEX AND STA2_INDEX = ar2.STA_INDEX AND STA3_INDEX = ar3.STA_INDEX"%tbl return make_dictionary(db, maker, query, lambda r:r[0:3]) def plot_trend_val(db, name, axes=None, setup=None, base=None, **kwargs): if axes is None: axes = plt.gca() name, name_err, tbl = quantity_lookup[name] markers = ["o","s","x","2","1"] colors = list("bgrcmy") ncolor = len(colors) nmarkers = len(markers) #setups = db.get_values(["setup_keys", "setup_vals"], tbls=["setups"]) #for i,(skeys, svals) in enumerate(setups): # setup = i keys = ["mean(%s, WImin, WImax)"%name] if name_err: keys += ["mean(%s, WImin, WImax)"%name_err] keys += ["MJD", "TARGET", "ESO INS SPEC RES", "ESO INS POLA MODE", "ESO INS TIM2 PERIOD", "ESO DET2 SEQ1 DIT"] data = db.get_values(keys, tbls=[tbl, "waveindex", "targets", "headers"], inside="recarray", base=base, **kwargs ) setups = np.array([r+"_"+p+"_"+t1+"_"+t2 for r,p,t1,t2 in zip(data["ESO INS SPEC RES"], data["ESO INS POLA MODE"],data["ESO INS TIM2 PERIOD"], data["ESO DET2 SEQ1 DIT"])]) setupset = set(setups) axes.targets = [] for i, setup in enumerate(setupset): ou, = np.where(setups==setup) subdata = data[ou] targets = set(subdata['TARGET']) for j,target in enumerate(targets): ou, = np.where(subdata['TARGET']==target) d = subdata[ou] color = colors[j%ncolor] marker = markers[i%nmarkers] fmt = color+marker if name_err: axes.errorbar(d["MJD"],d[name], yerr=d[name_err], label=target, color=color, ecolor=color, marker=marker, linestyle="none") else: axes.plot(d["MJD"],d[name], fmt, label=target) axes.targets.append( (np.min(d["MJD"]), target) ) return axes def plot_vis2(db, legbase="", **kwargs): a = plot_trend_val(db, "VIS2DATA", **kwargs) a.set_ylim(-0.1, 1.2) a.set_ylabel("$Vis^2$ ") a.set_xlabel("MJD") plot_base_legend(a, legbase) a.grid() return a def plot_visAmp(db, legbase="", **kwargs): a = plot_trend_val(db, "VISAMP", **kwargs) a.set_ylim(-0.1, 1.2) a.set_ylabel("$VisAmp$ ") a.set_xlabel("MJD") plot_base_legend(a, legbase) a.grid() return a def plot_t3phi(db, legbase="", **kwargs): a = plot_trend_val(db, "T3PHI", **kwargs) a.set_ylim(-190, 190) a.set_ylabel("$T3phi [deg]$ ") a.set_xlabel("MJD") plot_base_legend(a, legbase) a.grid() return a def plot_base_legend(axes, txt): axes.text(0.02, 0.9, txt, horizontalalignment='left', verticalalignment='center', transform=axes.transAxes) def plot_target_legend(axes, ypos=1.0, **kwargs): targets = getattr(axes,"targets", []) kwargs.setdefault("rotation", 70) for mjd, name in targets: axes.text(mjd, ypos, name , **kwargs) def legend_figure(fig, pos="upper right", **kwargs): legs = [(l,l.get_label()) for l in fig.axes[0].lines if not l.get_label().startswith("_")] legs = list(zip(*legs))+[pos] fig.legend(*legs,**kwargs) def plot_all(db, plot_func, plotname="", version="", ext=".pdf", save=False, **kwargs): kwargs.pop("DET_NAME", None) kwargs.pop("base", None) configs_data = db.get_values(["STA_INDEX", "TEL_NAME", "STA_NAME"], tbls=["arrays"], inside="recarray") #patche configs_data = configs_data[ np.array( [tel.startswith("AT") for tel in configs_data["TEL_NAME"]] ) ] stations = configs_data["STA_INDEX"] # bases = [] # bnames = [] # for i,sta1 in enumerate(stations): # for j,sta2 in enumerate(stations[i+1:], start=i+1): # N = len(db.get_values(["MJD"], tbls=["vis2","arrays"], base=(sta1,sta2))) # if N: # bases.append((sta1,sta2)) # bnames.append(configs_data[i]["STA_NAME"]+configs_data[j]["STA_NAME"]) # bases= [(10, 13), (10, 5), (10, 1), (13, 5), (13, 1), (5, 1)] bnames = ['B2A0','C1A0','C1B2','C1D0','D0A0','D0B2'] fig_ft, subplots_ft = plt.subplots(len(bases),1, sharex = True) fig_sc, subplots_sc = plt.subplots(len(bases),1, sharex = True) fig_ft.subplots_adjust(hspace=0.0) fig_sc.subplots_adjust(hspace=0.0) for axes_sc, axes_ft, base, bname in zip(subplots_sc.flat, subplots_ft.flat, bases, bnames): log.notice("Ploting base %s,%s"%base) plot_func(db, base=base, axes=axes_sc, legbase=bname, DET_NAME="sc", **kwargs) plot_func(db, base=base, axes=axes_ft, legbase=bname, DET_NAME="ft", **kwargs) fig_sc.filename = plotname+version+"_SC"+ext fig_ft.filename = plotname+version+"_FT"+ext if save: if not isinstance(save, str): save = "./" for fig in [fig_sc, fig_ft]: fig.set_size_inches(8.267,11.692) # A4 paper fig.suptitle(fig.filename) fig.savefig(save+"/"+fig.filename, orientation='portrait', papertype="a4") log.notice(save+"/"+fig.filename+" saved") return fig_sc, fig_ft def plot_all_trending(db, **kwargs): log.notice("Plotting VIS2 trend for SC and FT ") plot_all(db, plot_vis2, plotname=kwargs.pop("plotname","VIS2"), **kwargs) log.notice("Plotting VISAMP trend for SC and FT ") plot_all(db, plot_visAmp, plotname=kwargs.pop("plotname","VISAMP"), **kwargs) def thibase(stations): return "ar1.STA_NAME='"+stations[0]+"' and ar2.STA_NAME='"+stations[1]+"'" def plot_all_trending_new(db): # list of existing bases (discard the 'S' station) # base = zip(*db.execute("select distinct BASENAME from vis2 where BASENAME not like 'S%'").fetchall())[0] baselist = db.execute("select distinct ar1.STA_NAME, ar2.STA_NAME from vis2,arrays as ar1,arrays as ar2 where ar1.[FILEID]=vis2.[FILEID] and ar2.[FILEID]=vis2.[FILEID] and ar1.STA_INDEX=vis2.STA1_INDEX and ar2.STA_INDEX=vis2.STA2_INDEX").fetchall() baselist = [ (i,j) for i,j in baselist if i[0]!='S'] # VIS2 for SC and FT fig, subplots = plt.subplots(6, 1, sharex = True) fig.subplots_adjust(hspace=0.0) fig.set_size_inches(8.267,11.692) fig.suptitle("VIS2 FT (red) and SC (blue)") for i,axes in enumerate(subplots): plot_couple(db,"vis2","MJD","VIS2DATA_MED",yerr="VIS2ERR_MED", # yfunc=np.median,eyfunc=np.median, axes=axes, const="and det(vis2.INSNAME)='FT' and "+thibase(baselist[i]), marker='o',c='r') plot_couple(db,"vis2","MJD","VIS2DATA_MED",yerr="VIS2ERR_MED", # yfunc=np.median,eyfunc=np.median, axes=axes, const="and det(vis2.INSNAME)='SC' and "+thibase(baselist[i]), marker='+',c='b') axes.set_ylim(-0.1, 1.2) axes.grid() axes.set_ylabel("VIS2 "+baselist[i][0]+baselist[i][1]) axes.set_xlabel("MJD") fig.savefig("VIS2_FT_SC.png", orientation='portrait', papertype="a4") log.notice("VIS2_FT_SC.png saved") # VISAMP for SC and FT fig, subplots = plt.subplots(6, 1, sharex = True) fig.subplots_adjust(hspace=0.0) fig.set_size_inches(8.267,11.692) fig.suptitle("VISAMP FT (red) and SC (blue)") for i,axes in enumerate(subplots): plot_couple(db,"vis","MJD","VISAMP_MED",yerr="VISAMPERR_MED", # yfunc=np.median,eyfunc=np.median, axes=axes, const="and det(vis.INSNAME)='FT' and "+thibase(baselist[i]), marker='o',c='r') plot_couple(db,"vis","MJD","VISAMP_MED",yerr="VISAMPERR_MED", # yfunc=np.median,eyfunc=np.median, axes=axes, const="and det(vis.INSNAME)='SC' and "+thibase(baselist[i]), marker='+',c='b') axes.set_ylim(-0.1, 1.2) axes.grid() axes.set_ylabel("VISAMP "+baselist[i][0]+baselist[i][1]) axes.set_xlabel("MJD") fig.savefig("VISAMP_FT_SC.png", orientation='portrait', papertype="a4") log.notice("VISAMP_FT_SC.png saved") # VISPHI for SC and FT fig, subplots = plt.subplots(6, 1, sharex = True) fig.subplots_adjust(hspace=0.0) fig.set_size_inches(8.267,11.692) fig.suptitle("VISPHI FT (red) and SC (blue)") for i,axes in enumerate(subplots): plot_couple(db,"vis","MJD","VISPHI_MED",yerr="VISPHIERR_MED", # yfunc=np.median,eyfunc=np.median, axes=axes, const="and det(vis.INSNAME)='FT' and "+thibase(baselist[i]), marker='o',c='r') plot_couple(db,"vis","MJD","VISPHI_MED",yerr="VISPHIERR_MED", # yfunc=np.median,eyfunc=np.median, axes=axes, const="and det(vis.INSNAME)='SC' and "+thibase(baselist[i]), marker='+',c='b') # axes.set_ylim(-0.1, 1.2) axes.grid() axes.set_ylabel("VISPHI "+baselist[i][0]+baselist[i][1]) axes.set_xlabel("MJD") fig.savefig("VISPHI_FT_SC.png", orientation='portrait', papertype="a4") log.notice("VISPHI_FT_SC.png saved") # # VISPHI-POLAR-DIFF for SC and FT # fig, subplots = plt.subplots(6, 1, sharex = True) # fig.subplots_adjust(hspace=0.0) # fig.set_size_inches(8.267,11.692) # fig.suptitle("VISPHI FT (red) and SC (blue)") # # for i,axes in enumerate(subplots): # plot_couple(db,"vis","vis.VISPHI","vis.VISPHI - vis_p2.VISPHI", #yerr="vis.VISPHIERR", # yfunc=np.median,xfunc=np.median,axes=axes, # tbls=",vis as vis_p2", # const="and vis.BASENAME='"+base[i]+"' and vis.BASENAME=vis_p2.BASENAME and vis.INSNAME='SPECTRO_FT_P1' and vis_p2.INSNAME='SPECTRO_FT_P2' and vis.FILEID=vis_p2.FILEID and vis.MJD=vis_p2.MJD", # marker='o',c='r') # #plot_couple(db,"vis","vis.VISPHI","vis_p2.VISPHI", #yerr="vis.VISPHIERR", # # yfunc=np.median,xfunc=np.median,axes=axes, # # tbls=",vis as vis_p2", # # const="and vis.BASENAME='"+base[i]+"' and vis.BASENAME=vis_p2.BASENAME and vis.INSNAME='SPECTRO_SC_P1' and vis_p2.INSNAME='SPECTRO_SC_P2' and vis.FILEID=vis_p2.FILEID and vis.MJD=vis_p2.MJD", # # marker='+',c='b') # # # axes.set_ylim(-0.1, 1.2) # axes.grid() # axes.set_ylabel("PHIDIFF "+base[i]) # # axes.set_xlabel("MJD") # fig.savefig("VISPHI_PDIFF_FT_SC.png", orientation='portrait', papertype="a4") # log.notice("VISPHI_PDIFF_FT_SC.png saved") # # T3PHI # triplets = zip(*db.execute("select distinct BASENAME from t3 where BASENAME not like 'S%'").fetchall())[0] # # fig, subplots = plt.subplots(len(triplets), 1, sharex = True) # fig.subplots_adjust(hspace=0.0) # fig.set_size_inches(8.267,11.692) # fig.suptitle("T3PHI FT (red) and SC (blue)") # # for i,axes in enumerate(subplots): # plot_couple(db,"t3","MJD","T3PHI",yerr="T3PHIERR", # yfunc=np.median,eyfunc=np.median,axes=axes, # const="and det(t3.INSNAME)='FT' and "+thibase(baselist[i]), # marker='o',c='r') # # plot_couple(db,"t3","MJD","T3PHI",yerr="T3PHIERR", # yfunc=np.median,eyfunc=np.median, axes=axes, # const="and det(t3.INSNAME)='SC' and "+thibase(baselist[i]), # marker='+',c='b') # # axes.set_ylim(-190, 190) # axes.grid() # axes.set_ylabel("T3PHI "+triplets[i]) # # axes.set_xlabel("MJD") # fig.savefig("T3PHI_FT_SC.png", orientation='portrait', papertype="a4") # log.notice("T3PHI_FT_SC.png saved") # # # FLUX # tel = zip(*db.execute("select distinct BASENAME from flux where BASENAME not like 'S%'").fetchall())[0] # # fig, subplots = plt.subplots(len(tel), 1, sharex = True) # fig.subplots_adjust(hspace=0.0) # fig.set_size_inches(8.267,11.692) # fig.suptitle("FLUX FT (red) and SC (blue)") # # for i,axes in enumerate(subplots): # plot_couple(db,"flux","MJD","FLUX",yerr="FLUXERR", # yfunc=np.median,eyfunc=np.median,axes=axes, # const="and det(flux.INSNAME)='FT' and BASENAME='"+tel[i]+"'", # marker='o',c='r') # # plot_couple(db,"flux","MJD","FLUX",yerr="FLUXERR", # yfunc=np.median,eyfunc=np.median, axes=axes, # const="and det(flux.INSNAME)='SC' and BASENAME='"+tel[i]+"'", # marker='+',c='b') # # axes.grid() # axes.set_ylabel("FLUX "+tel[i]) # axes.set_yscale('log') # # axes.set_xlabel("MJD") # fig.savefig("FLUX_FT_SC.png", orientation='portrait', papertype="a4") # log.notice("FLUX_FT_SC.png saved") def plot_all_correlations(db): fig, subplots = plt.subplots(3, 2) fig.set_size_inches(8.267,11.692) # A4 paper fig.subplots_adjust(wspace=0.3,hspace=0.3) axes = subplots[0][0] plot_couple(db,"vis","vis.VISAMP","vis_ft.VISAMP",yerr="vis_ft.VISAMPERR",xerr="vis.VISAMPERR", yfunc=np.median, xfunc=np.median, eyfunc=np.median, exfunc=np.median, axes=axes, tbls=",vis as vis_ft", const=" and vis.[FILEID]=vis_ft.[FILEID] and vis.[BASENAME]=vis_ft.[BASENAME] and vis.[INSNAME]='SPECTRO_SC_P1' and vis_ft.[INSNAME]='SPECTRO_FT_P1' ", marker='o',c='g') axes.grid() axes.set_ylim(-0.1, 1.2) axes.set_xlim(-0.1, 1.2) axes.set_xlabel("VISAMP SC") axes.set_ylabel("VISAMP FT") axes=subplots[0][1] plot_couple(db,"vis2","vis2.VIS2DATA","vis2_ft.VIS2DATA",yerr="vis2_ft.VIS2ERR",xerr="vis2.VIS2ERR", yfunc=np.median, xfunc=np.median, eyfunc=np.median, exfunc=np.median, axes=axes, tbls=",vis2 as vis2_ft", const=" and vis2.[FILEID]=vis2_ft.[FILEID] and vis2.[BASENAME]=vis2_ft.[BASENAME] and vis2.[INSNAME]='SPECTRO_SC_P1' and vis2_ft.[INSNAME]='SPECTRO_FT_P1'", marker='o',c='g') axes.grid() axes.set_ylim(-0.1, 1.2) axes.set_xlim(-0.1, 1.2) axes.set_xlabel("VIS2 SC") axes.set_ylabel("VIS2 FT") axes=subplots[1][1] plot_couple(db,"vis","vis.VISAMP","vis2.VIS2DATA",xerr="vis.VISAMPERR",yerr="vis2.VIS2ERR", yfunc=np.median, xfunc=np.median, eyfunc=np.median, exfunc=np.median, axes=axes, tbls=",vis2", const=" and vis.[FILEID]=vis2.[FILEID] and vis.[BASENAME]=vis2.[BASENAME] and vis.[INSNAME]=vis2.[INSNAME] and vis.[INSNAME] like 'SPECTRO_FT_%'", marker='o',c='r') plot_couple(db,"vis","vis.VISAMP","vis2.VIS2DATA",xerr="vis.VISAMPERR",yerr="vis2.VIS2ERR", tbls=",vis2", yfunc=np.median, xfunc=np.median, eyfunc=np.median, exfunc=np.median, axes=axes, const=" and vis.[FILEID]=vis2.[FILEID] and vis.[BASENAME]=vis2.[BASENAME] and vis.[INSNAME]=vis2.[INSNAME] and vis.[INSNAME] like 'SPECTRO_SC_%'", marker='+',c='b') axes.grid() axes.set_ylim(-0.1, 1.2) axes.set_xlim(-0.1, 1.2) axes.set_xlabel("VISAMP") axes.set_ylabel("VIS2DATA") # VIS2DATA between polars axes=subplots[2][1] plot_couple(db,"vis2","vis2.VIS2DATA","vis2_p2.VIS2DATA",xerr="vis2.VIS2ERR",yerr="vis2_p2.VIS2ERR", yfunc=np.median, xfunc=np.median, eyfunc=np.median, exfunc=np.median, axes=axes, tbls=",vis2 as vis2_p2", const=" and vis2.[FILEID]=vis2_p2.[FILEID] and vis2.[BASENAME]=vis2_p2.[BASENAME] and vis2.[INSNAME]='SPECTRO_SC_P1' and vis2_p2.[INSNAME]='SPECTRO_SC_P2'", marker='o',c='r') plot_couple(db,"vis2","vis2.VIS2DATA","vis2_p2.VIS2DATA",xerr="vis2.VIS2ERR",yerr="vis2_p2.VIS2ERR", yfunc=np.median, xfunc=np.median, eyfunc=np.median, exfunc=np.median, axes=axes, tbls=",vis2 as vis2_p2", const=" and vis2.[FILEID]=vis2_p2.[FILEID] and vis2.[BASENAME]=vis2_p2.[BASENAME] and vis2.[INSNAME]='SPECTRO_FT_P1' and vis2_p2.[INSNAME]='SPECTRO_FT_P2'", marker='+',c='b') axes.grid() axes.set_ylim(-0.1, 1.2) axes.set_xlim(-0.1, 1.2) axes.set_xlabel("VIS2 P1") axes.set_ylabel("VIS2 P2") # VISAMP between polars axes=subplots[2][0] plot_couple(db,"vis","vis.VISAMP","vis_p2.VISAMP",xerr="vis.VISAMPERR",yerr="vis_p2.VISAMPERR", yfunc=np.median, xfunc=np.median, eyfunc=np.median, exfunc=np.median, axes=axes, tbls=",vis as vis_p2", const=" and vis.[FILEID]=vis_p2.[FILEID] and vis.[BASENAME]=vis_p2.[BASENAME] and vis.[INSNAME]='SPECTRO_SC_P1' and vis_p2.[INSNAME]='SPECTRO_SC_P2'", marker='o',c='r') plot_couple(db,"vis","vis.VISAMP","vis_p2.VISAMP",xerr="vis.VISAMPERR",yerr="vis_p2.VISAMPERR", yfunc=np.median, xfunc=np.median, eyfunc=np.median, exfunc=np.median, axes=axes, tbls=",vis as vis_p2", const=" and vis.[FILEID]=vis_p2.[FILEID] and vis.[BASENAME]=vis_p2.[BASENAME] and vis.[INSNAME]='SPECTRO_FT_P1' and vis_p2.[INSNAME]='SPECTRO_FT_P2'", marker='+',c='b') axes.grid() axes.set_ylim(-0.1, 1.2) axes.set_xlim(-0.1, 1.2) axes.set_xlabel("VISAMP P1") axes.set_ylabel("VISAMP P2") fig.savefig("Correlations.png", orientation='portrait', papertype="a4") log.notice("Correlations.png saved") def plot_all_uv(db): fig, subplots = plt.subplots(3, 2) fig.set_size_inches(8.267,11.692) # A4 paper fig.subplots_adjust(wspace=0.3,hspace=0.3) axes = subplots[0][0] plot_couple(db,"vis","UCOORD","VCOORD", axes=axes, const=" and vis.INSNAME like '%FT%'", marker='+',c='b') plot_couple(db,"vis","-UCOORD","-VCOORD", axes=axes, const=" and vis.INSNAME like '%FT%'", marker='+',c='b') axes.set_xlabel("UCOORD FT") axes.set_ylabel("VCOORD FT") axes.grid() axes = subplots[0][1] plot_couple(db,"vis","UCOORD","VCOORD", axes=axes, const=" and vis.INSNAME like '%SC%'", marker='o',c='r') plot_couple(db,"vis","-UCOORD","-VCOORD", axes=axes, const=" and vis.INSNAME like '%SC%'", marker='o',c='r') axes.set_xlabel("UCOORD SC") axes.set_ylabel("VCOORD SC") axes.grid() fig.savefig("uv.png", orientation='portrait', papertype="a4") log.notice("uv.png saved")