def make_charts():
chdir()
# Display options for numpy and pandas
set_display_options()
update_all_labels_with_cal_range(ug_chart_items, mass_calibration_ranges, ["50", "1700"])
update_all_labels_with_cal_range(mg_chart_items, mass_calibration_ranges, ["50", "1700"])
# Filter samples, reorder and rename
ug_target_samples = sort_n_filter_by_filename(all_samples, ug_chart_items)
ug_identified_compounds = ug_target_samples.get_compounds()
# Filter samples, reorder and rename
mg_target_samples = sort_n_filter_by_filename(all_samples, mg_chart_items)
mg_identified_compounds = mg_target_samples.get_compounds()
all_identified_compounds = sorted({*ug_identified_compounds, *mg_identified_compounds})
# Remove nitrobenzene
all_identified_compounds.remove("Nitrobenzene")
warn_if_all_filtered(ug_target_samples, ["Nitrobenzene"])
warn_if_all_filtered(mg_target_samples, ["Nitrobenzene"])
fig, ax = create_figure(tex_page, left=0.155, top=0.09)
fig, ax = plot_areas(fig, ax, ug_target_samples, all_identified_compounds, include_none=True, show_scores=True, legend_cols=3)
fig.suptitle("Peak Areas and Scores for Alliant Unique Propellant", fontsize=14, y=0.985)
# fig.set_size_inches(A4_portrait)
# fig.tight_layout()
# fig.subplots_adjust(bottom=0.13, top=0.91)
savefig(fig, "charts/propellant_5ul_injection_micro.png", dpi=300)
savefig(fig, "charts/propellant_5ul_injection_micro.svg")
fig, ax = create_figure(tex_page, left=0.155, top=0.09)
fig, ax = plot_areas(fig, ax, mg_target_samples, all_identified_compounds, include_none=True, show_scores=True, legend_cols=3)
fig.suptitle("Peak Areas and Scores for Alliant Unique Propellant", fontsize=14, y=0.985)
# fig.set_size_inches(A4_portrait)
# fig.tight_layout()
# fig.subplots_adjust(bottom=0.13, top=0.91)
savefig(fig, "charts/propellant_5ul_injection_milli.png", dpi=300)
savefig(fig, "charts/propellant_5ul_injection_milli.svg")
# plt.show()
fig, ax = create_figure(tex_page, left=0.15, bottom=0.17)
fig, ax = plot_retention_times(fig, ax, ug_target_samples, ug_target_samples.get_compounds(), legend_cols=3)
ax.set_ylabel("Concentration and Conditions")
fig, ax = create_figure(tex_page, left=0.15, bottom=0.17)
fig, ax = plot_retention_times(fig, ax, mg_target_samples, mg_target_samples.get_compounds(), legend_cols=3)
ax.set_ylabel("Concentration and Conditions")
plt.show()
def make_charts():
chdir()
# Display options for numpy and pandas
set_display_options()
update_all_labels_with_cal_range(chart_items, mass_calibration_ranges,
["50", "1700"])
# Filter samples, reorder and rename
target_samples = sort_n_filter_by_filename(all_samples, chart_items)
all_identified_compounds: List[str] = target_samples.get_compounds()
# Remove nitrobenzene
all_identified_compounds.remove("Nitrobenzene")
warn_if_all_filtered(target_samples, ["Nitrobenzene"])
# fig, ax = create_figure(tex_page_landscape, left=0.165, bottom=0.17) # without units
fig, ax = create_figure(tex_page_landscape,
left=0.135,
bottom=0.17,
top=0.09)
fig, ax = plot_areas(fig,
ax,
target_samples,
all_identified_compounds,
show_scores=True,
legend_cols=4,
mz_range=(50, 1700)) # , include_none=True)
# fig.suptitle("Peak Areas and Scores for Alliant Unique Propellant", fontsize=14, y=0.985)
ax.set_ylabel("Concentration and Conditions")
savefig(fig, "charts/benito_method_perms_propellant.png", dpi=600)
savefig(fig, "charts/benito_method_perms_propellant.svg")
# plt.show()
fig, ax = create_figure(tex_page, left=0.215, bottom=0.13, top=0.02)
fig, ax = plot_retention_times(fig,
ax,
target_samples,
target_samples.get_compounds(),
legend_cols=3)
ax.set_ylabel("Concentration and Conditions")
rt_data = make_rt_dataframe(target_samples.get_compounds(), target_samples)
for compound, data in rt_data.iteritems():
print(compound)
stdev = numpy.nanstd(data)
mean = numpy.nanmean(data)
print(mean)
rsd = stdev / mean
print(f"{rsd:.3%}")
print()
savefig(fig, "charts/benito_method_perms_propellant_rt.png", dpi=600)
savefig(fig, "charts/benito_method_perms_propellant_rt.svg")
def make_charts():
chdir()
# Display options for numpy and pandas
set_display_options()
update_all_labels_with_cal_range(chart_items, mass_calibration_ranges,
["50", "1700"])
# Filter samples, reorder and rename
target_samples = sort_n_filter_by_filename(all_samples, chart_items)
all_identified_compounds = target_samples.get_compounds()
# Remove nitrobenzene
# all_identified_compounds.remove("Nitrobenzene")
warn_if_all_filtered(target_samples, ["Nitrobenzene"])
fig, ax = create_figure(tex_page_landscape, left=0.12)
fig, ax = plot_areas(fig,
ax,
target_samples,
all_identified_compounds,
include_none=True,
show_scores=True)
fig.suptitle("Peak Areas and Scores for Alliant Unique Propellant",
fontsize=14,
y=0.985)
# fig.subplots_adjust(bottom=0.11, top=0.90)
savefig(fig, "charts/first_4_propellant_pos_and_neg.png", dpi=300)
savefig(fig, "charts/first_4_propellant_pos_and_neg.svg")
# plt.show()
# worklist = load_json_worklist("data/worklist.json")
# print(worklist)
#
# print(worklist.loc["Methanol Blank"])
# print(worklist.loc[worklist["Sample Name"] == "Methanol Blank"])
# print(worklist.loc[worklist["Sample Name"].str.startswith("Methanol")])
fig, ax = create_figure(tex_page, left=0.15, bottom=0.17)
fig, ax = plot_retention_times(fig,
ax,
target_samples,
target_samples.get_compounds(),
legend_cols=3)
fig.suptitle("Retention Times for Alliant Unique Propellant",
fontsize=14,
y=0.985)
ax.set_ylabel("Concentration and Conditions")
plt.show()
def make_charts():
chdir()
# Display options for numpy and pandas
set_display_options()
# for item in chart_items:
# print(mass_calibration_ranges[item.filename])
# print(item.new_name)
update_all_labels_with_cal_range(chart_items, mass_calibration_ranges,
["50", "1700"])
# Filter samples, reorder and rename
target_samples = sort_n_filter_by_filename(all_samples, chart_items)
all_identified_compounds = target_samples.get_compounds()
# Remove nitrobenzene
all_identified_compounds.remove("Nitrobenzene")
warn_if_all_filtered(target_samples, ["Nitrobenzene"])
fig, ax = create_figure(tex_page_landscape, left=0.23)
fig, ax = plot_areas(fig,
ax,
target_samples,
all_identified_compounds,
include_none=True,
show_scores=True)
fig.suptitle(
"Peak Areas and Scores for Standards with Reduced Flow Rate",
fontsize=14,
y=0.985,
) # Put actual number
ax.set_ylabel("Concentration and Conditions")
# fig.subplots_adjust(bottom=0.11, top=0.90)
# fig.set_size_inches(to_inch(A4_landscape))
# fig.tight_layout()
# fig.subplots_adjust(bottom=0.11, top=0.90)
savefig(fig, "charts/standards_low_flow.png", dpi=300)
savefig(fig, "charts/standards_low_flow.svg")
def make_charts():
chdir()
# Display options for numpy and pandas
set_display_options()
# update_all_labels_with_cal_range(chart_items, mass_calibration_ranges, ["50", "1700"])
# Filter samples, reorder and rename
target_samples = sort_n_filter_by_filename(all_samples, chart_items)
all_identified_compounds = target_samples.get_compounds()
# Remove nitrobenzene
all_identified_compounds.remove("Nitrobenzene")
warn_if_all_filtered(target_samples, ["Nitrobenzene"])
# fig, ax = create_figure(tex_page_landscape, left=0.2) # With m/z Range indicated
fig, ax = create_figure(tex_page_landscape, left=0.125,
top=0.09) # Without m/z Range indicated
fig, ax = plot_areas(
fig,
ax,
target_samples,
all_identified_compounds,
show_scores=True,
mz_range=(100, 3200)) # , include_none=True, legend_cols=3)
# fig.suptitle("Peak Areas and Scores for Mixed Standard", fontsize=14, y=0.985)
ax.set_ylabel("Concentration and Conditions")
savefig(fig, "charts/mixed_standards.png", dpi=600)
savefig(fig, "charts/mixed_standards.svg")
# plt.show()
fig, ax = create_figure(tex_page, left=0.15, bottom=0.17)
fig, ax = plot_retention_times(fig,
ax,
target_samples,
target_samples.get_compounds(),
legend_cols=3)
ax.set_ylabel("Concentration and Conditions")
# OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE
# OR OTHER DEALINGS IN THE SOFTWARE.
#
# stdlib
import pathlib
import re
# 3rd party
from mathematical.data_frames import set_display_options
from mathematical.utils import concatenate_csv
from mh_utils.csv_parser import ResultParser
from mh_utils.csv_parser.utils import concatenate_json
# Display options for numpy and pandas
set_display_options()
json_results_dir = pathlib.Path("../data/json_results")
raw_results_dir = pathlib.Path("../data/raw_results")
csv_results_dir = pathlib.Path("../data/csv_results")
parser = ResultParser(raw_results_dir, json_results_dir, csv_results_dir)
dates = {
"191121",
"191126",
"191128",
"191206",
"191211",
"200124",
"200128",
def make_charts():
chdir()
# Display options for numpy and pandas
set_display_options()
update_all_labels_with_cal_range(ec_dpa_chart_items,
mass_calibration_ranges, ["50", "1700"])
# Filter samples, reorder and rename
ec_dpa_target_samples = sort_n_filter_by_filename(all_samples,
ec_dpa_chart_items)
ec_dpa_identified_compounds = ec_dpa_target_samples.get_compounds()
# Remove nitrobenzene
ec_dpa_identified_compounds.remove("Nitrobenzene")
warn_if_all_filtered(ec_dpa_target_samples, ["Nitrobenzene"])
fig, ax = create_figure(tex_page_landscape,
left=0.15,
bottom=0.17,
top=0.1)
fig, ax = plot_areas(
fig,
ax,
ec_dpa_target_samples,
ec_dpa_identified_compounds,
include_none=True,
show_scores=True,
legend_cols=4,
show_score_in_legend=True,
)
# fig.suptitle("Peak Areas and Scores with Method 3", fontsize=14, y=0.985)
ax.set_ylabel("Concentration and Conditions")
fig.text(0.739, 0.026, "¹²³", fontsize=9, zorder=20)
fig.text(0.762, 0.026, "Repeat analyses", fontsize=9, zorder=20)
savefig(fig, "charts/new_method_standards.png", dpi=600)
savefig(fig, "charts/new_method_standards.svg")
# update_all_labels_with_cal_range(std_mix_chart_items, mass_calibration_ranges, ["50", "1700"])
# Filter samples, reorder and rename
std_mix_target_samples = sort_n_filter_by_filename(all_samples,
std_mix_chart_items)
std_mix_identified_compounds = std_mix_target_samples.get_compounds()
# Remove nitrobenzene
std_mix_identified_compounds.remove("Nitrobenzene")
warn_if_all_filtered(std_mix_target_samples, ["Nitrobenzene"])
# fig, ax = create_figure(tex_page_landscape, left=0.2, bottom=0.2) # With mz range
fig, ax = create_figure(tex_page_landscape, left=0.11, bottom=0.2,
top=0.1) # Without mz range
fig, ax = plot_areas(
fig,
ax,
std_mix_target_samples,
std_mix_identified_compounds,
include_none=True,
show_scores=True,
legend_cols=4,
# mz_range=(100, 3200)
show_score_in_legend=True,
)
# fig.suptitle("Peak Areas and Scores for Mixed Standard with Method 3", fontsize=14, y=0.985)
ax.set_ylabel("Concentration") # and Conditions
fig.text(0.637,
0.026,
"Calibration Range: $100-3200~m/z$",
fontsize=9,
zorder=20)
savefig(fig, "charts/new_method_mixed_standard.png", dpi=600)
savefig(fig, "charts/new_method_mixed_standard.svg")
