def test_cdf(): remote_link, local_filename = download._resolve_usi( "mzspec:MSV000086834:raw/20210210 GNPS LMCS/PA1MeOH1.aia.CDF") agg_dict, msn_results = lcms_map._aggregate_lcms_map( local_filename, 0, 100000, 0, 2000) lcms_map._create_map_fig(agg_dict, msn_results) print(local_filename)
def test_chromatograms(): usi = "mzspec:MSV000087058:peak/peak/std1_022721.mzML" remote_link, local_filename = download._resolve_usi(usi) chrom_list = xic.chromatograms_list(local_filename) xic_df = xic.get_chromatogram(local_filename, chrom_list[0]) assert (len(xic_df) > 300)
def test(): usi = "mzspec:MSV000085852:QC_0:scan:3548" remote_link, local_filename = download._resolve_usi(usi) all_xic_values = [["278.1902", 278.1902]] xic_tolerance = 0.5 xic_ppm_tolerance = 10 xic_tolerance_unit = "Da" rt_min = 2 rt_max = 8 polarity_filter = "Positive" xic_df, ms2_data = xic._xic_file_slow(local_filename, all_xic_values, xic_tolerance, xic_ppm_tolerance, xic_tolerance_unit, rt_min, rt_max, polarity_filter) xic_df["i"] = xic_df["XIC 278.1902"] xic_df["USI"] = 1 cvs = ds.Canvas(plot_width=100, plot_height=1) agg = cvs.points(xic_df, 'rt', 'USI', agg=ds.sum("i")) import plotly.express as px fig = px.imshow(agg, origin='lower', y=[usi], labels={'color': 'Log10(abundance)'}, height=600, template="plotly_white") fig.write_image("test.png")
def test_resolve_download_convert(): df = pd.read_csv("usi_list.tsv", sep='\t') for record in df.to_dict(orient="records"): print(record["usi"]) remote_link, local_filename = download._resolve_usi(record["usi"]) assert (os.path.exists(local_filename))
def test_xic_wrapper(): remote_link, local_filename = download._resolve_usi( "mzspec:MSV000085852:QC_0") all_xic_values = [["278.1902", 278.1902]] xic_tolerance = 0.5 xic_ppm_tolerance = 10 xic_tolerance_unit = "Da" rt_min = 5 rt_max = 6 polarity_filter = "Positive" xic.xic_file(local_filename, all_xic_values, xic_tolerance, xic_ppm_tolerance, xic_tolerance_unit, rt_min, rt_max, polarity_filter, get_ms2=True) xic.xic_file(local_filename, all_xic_values, xic_tolerance, xic_ppm_tolerance, xic_tolerance_unit, rt_min, rt_max, polarity_filter, get_ms2=False)
def test_scan_in_usi(): usi = "mzspec:MSV000085852:QC_0:scan:3548" remote_link, local_filename = download._resolve_usi(usi) current_map_selection, highlight_box = utils._resolve_map_plot_selection( None, usi) import sys print(current_map_selection, highlight_box, file=sys.stderr)
def test_2d_mapping_many(): df = pd.read_csv("usi_list.tsv", sep='\t') for record in df.to_dict(orient="records"): print(record["usi"]) remote_link, local_filename = download._resolve_usi(record["usi"]) agg_dict, msn_results = lcms_map._aggregate_lcms_map( local_filename, 0, 300, 0, 2000) lcms_map._create_map_fig(agg_dict, msn_results)
def test_2dmap_proteomics_data2(): remote_link, local_filename = download._resolve_usi("mzspec:MSV000083508:01308_H02_P013387_B00_N16_R1") min_rt = 0 max_rt = 1000000 min_mz = 0 max_mz = 2000 lcms_map._gather_lcms_data(local_filename, min_rt, max_rt, min_mz, max_mz, polarity_filter="None")
def _download_convert_file(usi, temp_folder="temp"): """ This function does the serialization of downloading files """ return_val = download._resolve_usi(usi, temp_folder=temp_folder) _convert_file_feather.delay(usi, temp_folder=temp_folder) return return_val
def test_2dmap_proteomics_data(): remote_link, local_filename = download._resolve_usi("mzspec:MSV000079514:Adult_CD4Tcells_bRP_Elite_28_f01") min_rt = 0 max_rt = 1000000 min_mz = 0 max_mz = 2000 lcms_map._gather_lcms_data(local_filename, min_rt, max_rt, min_mz, max_mz, polarity_filter="None")
def test_2dmap_metabolomics_data(): remote_link, local_filename = download._resolve_usi("mzspec:MSV000085852:QC_0") min_rt = 0 max_rt = 1000000 min_mz = 0 max_mz = 2000 lcms_map._gather_lcms_data(local_filename, min_rt, max_rt, min_mz, max_mz, polarity_filter="None")
def test_ms2_spectrum(): usi = "mzspec:MSV000085852:QC_0:scan:1" remote_link, local_filename = download._resolve_usi(usi) peaks, mz, spectrum_details_string = ms2._get_ms2_peaks( usi, local_filename, 1) assert (len(peaks) > 10) usi = "mzspec:MSV000086709:peak/27_Walterinnesia_egyptia_Liverpool_unkown_red_2.mzXML" remote_link, local_filename = download._resolve_usi(usi) peaks, mz, spectrum_details_string = ms2._get_ms2_peaks( usi, local_filename, 1729) assert (len(peaks) > 10) # Currently Doesnt work, but will need to. TODO: Fix usi = "mzspec:MSV000086995:updates/2021-04-01_mwang87_a4ef53e6/peak/wash_initial.mzML" remote_link, local_filename = download._resolve_usi(usi) peaks, mz, spectrum_details_string = ms2._get_ms2_peaks( usi, local_filename, 527060) assert (len(peaks) == 0) # This is known to have no peaks
def test_2dmap_proteomics_zoomed(): remote_link, local_filename = download._resolve_usi("mzspec:MSV000079514:Adult_CD4Tcells_bRP_Elite_28_f01") map_selection = {} map_selection["xaxis.range[0]"] = "10" map_selection["xaxis.range[1]"] = "15" map_selection["yaxis.range[0]"] = "500" map_selection["yaxis.range[1]"] = "1000" lcms_map._create_map_fig(local_filename, map_selection=map_selection)
def test_2dmap_metabolomics_zoomed(): remote_link, local_filename = download._resolve_usi("mzspec:MSV000085852:QC_0") map_selection = {} map_selection["xaxis.range[0]"] = "3" map_selection["xaxis.range[1]"] = "5" map_selection["yaxis.range[0]"] = "200" map_selection["yaxis.range[1]"] = "750" lcms_map._create_map_fig(local_filename, map_selection=map_selection)
def test_xic_metabolomics_slow(): remote_link, local_filename = download._resolve_usi("mzspec:MSV000085852:QC_0") all_xic_values = [["278.1902", 278.1902]] xic_tolerance = 0.5 xic_ppm_tolerance = 10 xic_tolerance_unit = "Da" rt_min = 5 rt_max = 6 polarity_filter = "Positive" xic._xic_file_slow(local_filename, all_xic_values, xic_tolerance, xic_ppm_tolerance, xic_tolerance_unit, rt_min, rt_max, polarity_filter)
def test_xic_proteomics_slow(): remote_link, local_filename = download._resolve_usi("mzspec:MSV000079514:Adult_CD4Tcells_bRP_Elite_28_f01") all_xic_values = [["1040.057006835938", 1040.057006835938]] xic_tolerance = 0.5 xic_ppm_tolerance = 10 xic_tolerance_unit = "Da" rt_min = 0 rt_max = 100000 polarity_filter = "Positive" xic._xic_file_slow(local_filename, all_xic_values, xic_tolerance, xic_ppm_tolerance, xic_tolerance_unit, rt_min, rt_max, polarity_filter)
def test_ms1_selection_spectrum(): usi = "mzspec:MSV000086521:raw/ORSL13CM.CDF" remote_link, local_filename = download._resolve_usi(usi) closest_scan = ms2.determine_scan_by_rt(usi, local_filename, 12.83) print("closest_scan", closest_scan) assert (int(closest_scan) > 0) peaks, mz, spectrum_details_string = ms2._get_ms2_peaks( usi, local_filename, 764) assert (len(peaks) > 10)
def test_feather_download_convert(): df = pd.read_csv("usi_list.tsv", sep='\t') for record in df.to_dict(orient="records"): print(record["usi"]) remote_link, local_filename = download._resolve_usi(record["usi"]) output_ms1_filename, output_msn_filename = lcms_map._get_feather_filenames( local_filename) lcms_map._save_lcms_data_feather(local_filename) # Making sure the filename exists assert (os.path.exists(output_ms1_filename)) # Making sure it includes polarity ms1_results = pd.read_feather(output_ms1_filename) assert ("polarity" in ms1_results)
def test_agilent(): remote_link, local_filename = download._resolve_usi( "mzspec:MSV000084060:KM0001") agg_dict, msn_results = lcms_map._aggregate_lcms_map( local_filename, 0, 300, 0, 2000) lcms_map._create_map_fig(agg_dict, msn_results)
def test_tic_fast(): df = pd.read_csv("usi_list.tsv", sep='\t') for record in df.to_dict(orient="records"): print(record["usi"]) remote_link, local_filename = download._resolve_usi(record["usi"]) tic._tic_file_fast(local_filename)
def test_2dmap_metabolomics(): remote_link, local_filename = download._resolve_usi("mzspec:MSV000085852:QC_0") lcms_map._create_map_fig(local_filename)
def test_2d_mapping(): remote_link, local_filename = download._resolve_usi( "mzspec:MSV000085852:QC_0") agg_dict, msn_results = lcms_map._aggregate_lcms_map( local_filename, 3, 7, 300, 500) lcms_map._create_map_fig(agg_dict, msn_results)
def test_2dmap_proteomics(): remote_link, local_filename = download._resolve_usi("mzspec:MSV000079514:Adult_CD4Tcells_bRP_Elite_28_f01") lcms_map._create_map_fig(local_filename)