def get_statistics(X, y):
"""
================
INPUT: array of X data (temperature), array of Y data (heat flow), int
OUTPUT: float, float, float, float, tuple
================
Returns four key release characteristics:
1. Enthalpy
2. Peak heat flow
3. Temperature at peak
4. Rough standard deviation of peak
5. Onset and end points
"""
peak_X, peak_y = pdetect.get_peak_X_y(X, y)
enthalpy = get_enthalpy(X, y)
peak_heat_flow = np.min(peak_y) # find the minimum y
peak_temp = peak_X[np.argmin(peak_y)] # find the x for which y is minimized
heat_flow_std = np.std(peak_y)
onset, end = pdetect.get_points_coordinates(X, y)
return enthalpy, peak_heat_flow, peak_temp, heat_flow_std, (onset, end)
def fit_line(X, y):
"""
================
INPUT: array of X data (temperature), array of Y data (heat flow)
OUTPUT: array of X data (temperature), array of Y data (best-fit-line heat
flow)
================
Returns two arrays, of the x's and y's of the best-fit-line.
"""
peak_X, peak_y = pdetect.get_peak_X_y(X, y)
onset_point, end_point = pdetect.get_points(X, y)
(x_0, y_0), (x_1, y_1) = pdetect.get_points_coordinates(X, y)
line_X, line_y = construct_line(x_0,
y_0,
x_1,
y_1,
peak_X
)
return line_X, line_y
def process_data(filepath, plot = False):
"""
================
INPUT: string (filepath), boolean
OUTPUT: several statistics, and a plot if "plot" parameter is True
================
Returns enthalpy about the data, and plots it, the endpoints and the
line if you want (as well as statistics)
"""
# clean the data
data = fh.clean_file(filepath)
#find the first number in the filename and use as the title
name_of_preparation = fh.get_file_title(filepath)
# ensure that the data is formatted correctly, as arrays
temp, heat_flow = np.array(data.temp), np.array(data.heat_flow)
# generate statistics
e, hf, t, sd, (onset_point, end_point) = pstats.get_statistics(temp, heat_flow)
statistics_text = """=== Preparation {0} ===
Enthalpy: {1}
Peak Heat Flow: {2}
Peak Temperature: {3}
Heat Flow Standard Devation: {4}
Onset point: {5}, {6}
End point: {7}, {8}
""".format(name_of_preparation,
round(e, 3),
round(hf, 3),
round(t, 2),
round(sd, 4),
round(onset_point[0], 2),
round(onset_point[1], 3),
round(end_point[0], 2),
round(end_point[1], 3)
)
if plot:
# get line for plotting
line_X, line_y = pstats.fit_line(temp, heat_flow)
# get onset and end points
(x0, y0), (x1, y1) = pdetect.get_points_coordinates(temp, heat_flow)
# set up plot
fig, ax = plt.subplots(1)
ax.set_title("Preparation {}".format(name_of_preparation))
ax.set_xlabel("Temperature")
ax.set_ylabel("Heat Flow")
ax.annotate(statistics_text,
xy=(0.5, 0.4),
xycoords='axes fraction'
)
# plot original data
plt.plot(temp,
heat_flow,
color = 'black',
label = "Original data"
)
# plot best fit line
plt.plot(line_X,
line_y,
color = 'red',
label = "Best fit line"
)
# plot onset point
plt.scatter(x0,
y0,
color = 'green',
label = 'Onset: {}, {}'.format(round(x0,2), round(y0, 2))
)
# plot end point
plt.scatter(x1,
y1,
color = 'purple',
label = 'End: {}, {}'.format(round(x1, 2), round(y1, 2))
)
plt.legend()
plt.show()
return e # this is short for enthalpy, as defined above
def process_data(filepath, plot=False):
"""
================
INPUT: string (filepath), boolean
OUTPUT: several statistics, and a plot if "plot" parameter is True
================
Returns enthalpy about the data, and plots it, the endpoints and the
line if you want (as well as statistics)
"""
# clean the data
data = fh.clean_file(filepath)
#find the first number in the filename and use as the title
name_of_preparation = fh.get_file_title(filepath)
# ensure that the data is formatted correctly, as arrays
temp, heat_flow = np.array(data.temp), np.array(data.heat_flow)
# generate statistics
e, hf, t, sd, (onset_point,
end_point) = pstats.get_statistics(temp, heat_flow)
statistics_text = """=== Preparation {0} ===
Enthalpy: {1}
Peak Heat Flow: {2}
Peak Temperature: {3}
Heat Flow Standard Devation: {4}
Onset point: {5}, {6}
End point: {7}, {8}
""".format(name_of_preparation, round(e, 3), round(hf, 3), round(t, 2),
round(sd, 4), round(onset_point[0], 2),
round(onset_point[1], 3), round(end_point[0], 2),
round(end_point[1], 3))
if plot:
# get line for plotting
line_X, line_y = pstats.fit_line(temp, heat_flow)
# get onset and end points
(x0, y0), (x1, y1) = pdetect.get_points_coordinates(temp, heat_flow)
# set up plot
fig, ax = plt.subplots(1)
ax.set_title("Preparation {}".format(name_of_preparation))
ax.set_xlabel("Temperature")
ax.set_ylabel("Heat Flow")
ax.annotate(statistics_text, xy=(0.5, 0.4), xycoords='axes fraction')
# plot original data
plt.plot(temp, heat_flow, color='black', label="Original data")
# plot best fit line
plt.plot(line_X, line_y, color='red', label="Best fit line")
# plot onset point
plt.scatter(x0,
y0,
color='green',
label='Onset: {}, {}'.format(round(x0, 2), round(y0, 2)))
# plot end point
plt.scatter(x1,
y1,
color='purple',
label='End: {}, {}'.format(round(x1, 2), round(y1, 2)))
plt.legend()
plt.show()
return e # this is short for enthalpy, as defined above