def plot_lifetime_for_power_dependence(db_conn, query, exp_dir, envir, title):
hanle_curve_fits = db_conn.spin_optics.hanle_curve_fits
query_vars = [
"probe_energy",
"sample_temperature",
"amplitude",
"inv_hwhm",
"probe_background",
"offset",
"pump_intensity",
]
fits = field_dataframe(hanle_curve_fits.find(query), query_vars)
print(fits)
fig, ax = plt.subplots()
plt.plot(fits["pump_intensity"], hanle_lifetime_gauss_in_sec(fits["inv_hwhm_0"], g=0.33), "^r", label="g = 0.33")
plt.plot(fits["pump_intensity"], hanle_lifetime_gauss_in_sec(fits["inv_hwhm_1"], g=2.7), "ok", label="g = 2.7")
ax.set_yticklabels(ax.get_yticks() / 1e-9)
ax.set_xticklabels(ax.get_xticks() / 1e-3)
plt.xlabel("Pump Intensity (milliwatts)")
plt.ylabel("Lifetime (ns)")
plt.title(title)
plt.legend()
plt.savefig(os.path.join(exp_dir, envir["eid"] + " lifetime vs. pump power.pdf"))
fits["lifetime_0_0.33 (sec)"] = hanle_lifetime_gauss_in_sec(fits["inv_hwhm_0"], g=0.33)
fits["lifetime_1_2.7 (sec)"] = hanle_lifetime_gauss_in_sec(fits["inv_hwhm_1"], g=2.7)
fits.columns = dimension_column_labels(fits.columns, db_conn)
fits.to_csv(os.path.join(exp_dir, envir["eid"] + " data vs. pump power.csv"))
def generate_hanle_params(
data,
file_key_column,
independent_variable_name,
search_dirs,
fit_paths,
file_key_format="%04d",
file_column_names=["Field", "X", "Y", "PDA", "FR", "Timestamp"],
mag_field_col_name="Field",
faraday_rot_col_name="FR",
X_col_name="X",
Y_col_name="Y",
model=double_lorentzian_centered_no_off,
fitter=opt.curve_fit,
):
hanle_model_cols = ["A1", "k1", "A2", "k2", "y0"]
for c in hanle_model_cols:
if not c in data:
data[c] = np.nan
def curve_loader(value):
rs = data[data[independent_variable_name] == value]
result = read_csv(
filename_containing_string_in_dirs(file_key_format % rs[file_key_column].iloc[0], search_dirs)
)
result.columns = file_column_names
if len(rs.index) > 1:
for i, r in rs[1:].iterrows():
d = read_csv(
filename_containing_string_in_dirs(file_key_format % rs[file_key_column].iloc[0], search_dirs)
)
d.columns = file_column_names
result = result.append(d)
return result
for init_p, path in fit_paths:
progressive_fit(
data,
curve_loader,
init_p,
hanle_model_cols,
model,
path,
key_name=independent_variable_name,
x_name=mag_field_col_name,
y_name=faraday_rot_col_name,
fitter=fitter,
)
data["L1"] = data[hanle_model_cols[1]].apply(lambda k: hanle_lifetime_gauss_in_sec(abs(k)))
data["L2"] = data[hanle_model_cols[3]].apply(lambda k: hanle_lifetime_gauss_in_sec(abs(k)))
# Calculate median phase of each Hanle curve and store it in the results
if not "MP" in data:
data["MP"] = np.nan
for i, r in data.iterrows():
d = read_csv(filename_containing_string_in_dirs(file_key_format % r[file_key_column], search_dirs))
d.columns = file_column_names
data.loc[i, "MP"] = np.median(np.arctan2(d[Y_col_name], d[X_col_name]))
def hanle_curve_title_from_params(fit_params, db_conn):
sample = db_conn.spin_optics.samples.find_one({"_id": fit_params["sample_id"]})
result = "Hanle Effect on $%s$\n" % sample["system"]
if "capping" in sample.keys():
result += 'Capping layer "%s"' % sample["capping"]
if "substrate" in sample.keys():
result += ', Substrate "%s"\n' % sample["substrate"]
else:
result += "\n"
result += "Pump %.2f eV @ %d $\mu W$ Probe %.2f eV @ %d $\mu W$\n" % (
fit_params["pump_energy"],
fit_params["pump_intensity"] * 1e6,
fit_params["probe_energy"],
fit_params["probe_intensity"] * 1e6,
)
result += "Temperature %.1f K\n" % fit_params["sample_temperature"]
for a, l, i in zip(fit_params["amplitude"], fit_params["inv_hwhm"], range(0, len(list(fit_params["amplitude"])))):
result += "Peak %d HWHM %d Gauss (g=1 lifetime is %.3fns\n" % (
i + 1,
1 / l,
1e9 * hanle_lifetime_gauss_in_sec(l),
)
result += "(SID %s, Measured %s)" % (sample["_id"], str(fit_params["when"]))
return result
