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)
