violin plot (02-01-2021)

def violin(kmeans_input=7,currents=False, title=True, data_processing=1, dpi=None, savepng=False):
    start = time.time()

    figsize = (30*0.75,15*0.75)
    fontsize = figsize[0]
    fig, ax = plt.subplots(figsize=figsize)

    scan_order = [185,183,181,182,186]

    xlabels = ["-200","-100","0","+100","+200"]

    if currents:
        if data_processing == 1:
            current_array1 = np.array(load_cache_currents()["pixelplotting_array"][scan_order.index(185)]).ravel()[np.newaxis,:].T
            current_array2 = np.array(load_cache_currents()["pixelplotting_array"][scan_order.index(183)]).ravel()[np.newaxis,:].T
            current_array3 = np.array(load_cache_currents()["pixelplotting_array"][scan_order.index(181)]).ravel()[np.newaxis,:].T
            current_array4 = np.array(load_cache_currents()["pixelplotting_array"][scan_order.index(182)]).ravel()[np.newaxis,:].T
            current_array5 = np.array(load_cache_currents()["pixelplotting_array"][scan_order.index(186)]).ravel()[np.newaxis,:].T
        if data_processing == 3:
            current_array1 = np.array(load_cache_currents()["pixelplotting_array_direct"][scan_order.index(185)]).ravel()[np.newaxis,:].T
            current_array1 = current_array1 - np.nanmin(current_array1)
            current_array2 = np.array(load_cache_currents()["pixelplotting_array_direct"][scan_order.index(183)]).ravel()[np.newaxis,:].T
            current_array2 = current_array2 - np.nanmin(current_array2)
            current_array3 = np.array(load_cache_currents()["pixelplotting_array_direct"][scan_order.index(181)]).ravel()[np.newaxis,:].T
            current_array3 = current_array3 - np.nanmin(current_array3)
            current_array4 = np.array(load_cache_currents()["pixelplotting_array_direct"][scan_order.index(182)]).ravel()[np.newaxis,:].T
            current_array4 = current_array4 - np.nanmin(current_array4)
            current_array5 = np.array(load_cache_currents()["pixelplotting_array_direct"][scan_order.index(186)]).ravel()[np.newaxis,:].T
            current_array5 = current_array5 - np.nanmin(current_array5
        numpy_data = np.concatenate((current_array1,current_array2,current_array3,current_array4,current_array5),axis=1)
        df = pd.DataFrame(data=numpy_data, columns=xlabels)
        ax = sn.violinplot(data=df, scale="count",inner="box")

    else:
        numpy_dataDic = {}
        for scan_index in scan_order:
            current_array_scan = np.array(load_cache_currents()["pixelplotting_array"][scan_order.index(scan_index)])
            data = current_array_scan.ravel()[np.newaxis,:].T
            scan = np.repeat(scan_index,len(data))[np.newaxis,:].T
            group = np.array(load_cache_kmeans(kmeans_input = kmeans_input)["2"]["cluster_numbers"]).ravel()[np.newaxis,:].T
            numpy_dataDic[scan_index] = np.concatenate((data,scan,group),axis=1)
            #plt.axvline(x=scan_index-181.5, color="grey", lw=1)
        numpy_data = np.concatenate((numpy_dataDic[185],numpy_dataDic[183],numpy_dataDic[181],numpy_dataDic[182],numpy_dataDic[186]))
        df = pd.DataFrame(data=numpy_data, columns=["XBIC","Bias voltage (mV)","Group"])
        df = df.replace(1.0,"Group 1")
        df = df.replace(2.0,"Group 2")
        ax = sn.violinplot(x = "Bias voltage (mV)", y = "XBIC", hue = "Group", data = df, order=[185,183,181,182,186], palette = "viridis", split=True, linewidth = 0, scale = "count", inner = "box", ax = ax)

    ax.set_xlabel("Bias voltage (mV)", labelpad = 10, fontsize=9/5*fontsize, fontweight="bold")
    ax.set_ylabel("XBIC", labelpad = 10, fontsize=9/5*fontsize, fontweight="bold")
    ax.tick_params(labelsize=fontsize, length=4/5*fontsize)

    ax.xaxis.set_ticks([0,1,2,3,4])
    ax.xaxis.set_ticklabels(xlabels, fontsize=fontsize)

    # add minor ticks for XBIC
    ax.yaxis.set_minor_locator(MultipleLocator(10))
    ax.tick_params(which='minor', length=2/5*fontsize)
    plt.grid(axis="y", which="minor",lw=0.25)

    plt.grid(axis="y")
    if title:
        plt.title("Current distribution", pad = 15, fontsize=round(9/5*fontsize), fontweight="bold")

    # add vertical lines
    for x in range(5):
        plt.axvline(x=x+0.5, color="grey", lw=1)

#     meta = {
#     "colour": {"a": "red", "b": "blue"},
#     "label": {"a": "this a", "b": "this b"},
#     }

#     handles = [
#         Patch(
#             facecolor=meta["colour"][x],
#             label=meta["label"][x],
#         )
#         for x in meta["colour"].keys()
#     ]

#     fig.legend(
#         handles=handles,
#         ncol=2,
#         loc="upper right",
#         bbox_to_anchor=(0.5, 0.5),
#         fontsize=10,
#         handlelength=1,
#         handleheight=1,
#         frameon=False,
#     )

    ax.legend(prop={'size': fontsize})
    #ax.get_legend().remove()

    plt.show()

    end = time.time()
    print(f"Plotting of the violin plots took {str(round(end-start,2))} seconds.")

    if savepng:
        now = datetime.now()
        dt_string = now.strftime("%d-%m-%Y_%H_%M_%S")
        if dpi is None:
            fig.savefig("savefig/violin_" + dt_string + ".png", dpi=fig.dpi, bbox_inches="tight")
        else:
            fig.savefig("savefig/violin_" + dt_string + ".png", dpi=dpi, bbox_inches="tight")