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Fig size and plot formatting
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@chris-ashe
chris-ashe committed Sep 26, 2023
1 parent 8e23c69 commit f68f71b
Showing 1 changed file with 76 additions and 58 deletions.
134 changes: 76 additions & 58 deletions process/io/plot_scans.py
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Original file line number Diff line number Diff line change
Expand Up @@ -30,7 +30,7 @@
import argparse
from argparse import RawTextHelpFormatter
from pathlib import Path
from numba import njit

# PROCESS libraries
import process.io.mfile as mf

Expand Down Expand Up @@ -124,20 +124,19 @@ def parse_args(args):
"list the same number of label names eg: -nl 'leg1 leg2'\n"
"(default = MFile file name) "
),

)

parser.add_argument(
"-2DC",
"--two_dimensional_contour",
action="store_true",
help=(
"Option to plot 2D scans as a coloured contour plot instead of a line plot \n "
"Note: Non convergent points will show up with a value of zero \n "
"Note: The scan paramters must both be in increasing orderl \n "
),

)

parser.add_argument(
"-stc",
"--stack_plots",
Expand All @@ -146,7 +145,6 @@ def parse_args(args):
"Option to plot multiple 1D plots in a column of sub0plots \n "
"Variables will be plotted in order of input"
),

)

return parser.parse_args(args)
Expand Down Expand Up @@ -401,7 +399,6 @@ def main(args=None):
m_file = mf.MFile(filename=input_files[-1])
nsweep_ref = int(m_file.data["nsweep"].get_scan(-1))
scan_var_name = nsweep_dict[nsweep_ref]

# Get the eventual second scan variable
nsweep_2_ref = int(0)
is_2D_scan = False
Expand Down Expand Up @@ -522,7 +519,6 @@ def main(args=None):
scan_var_array[input_file][ii] = m_file.data[scan_var_name].get_scan(
conv_i[ii]
)

# output list declaration
output_arrays[input_file] = dict()
output_arrays2[input_file] = dict()
Expand Down Expand Up @@ -553,7 +549,6 @@ def main(args=None):
for ii in range(n_scan):
ouput_array[ii] = m_file.data[output_name].get_scan(conv_i[ii])
output_arrays[input_file][output_name] = ouput_array

# Second variable scan
if output_names2 != []:
for output_name2 in output_names2:
Expand Down Expand Up @@ -607,9 +602,9 @@ def main(args=None):
# Plot section
# -----------
if stack_plots:
fig, axs = plt.subplots(len(output_names), 1, sharex=True, figsize=(8.0, 4.8))
fig.subplots_adjust(hspace=0.075)
#fig.tight_layout()
fig, axs = plt.subplots(len(output_names), 1, figsize=(8.0, 12.8))
fig.subplots_adjust(hspace=0.0)
# fig.tight_layout()
for output_name in output_names:
# reset counter for label_name
kk = 0
Expand Down Expand Up @@ -644,13 +639,13 @@ def main(args=None):
)
else:
if stack_plots:
axs[output_names.index(output_name)].plot(
axs[output_names.index(output_name)].plot(
scan_var_array[input_file],
output_arrays[input_file][output_name],
"--o",
color="blue" if output_names2 != [] else None,
label=labl,
)
)
else:
plt.plot(
scan_var_array[input_file],
Expand Down Expand Up @@ -690,18 +685,21 @@ def main(args=None):
plt.grid(True)
plt.xlabel(labels[scan_var_name], fontsize=axis_font_size)
plt.legend(
loc="lower center",
fontsize=legend_size,
bbox_to_anchor=(0.5, -1.7),
fancybox=True,
shadow=False,
ncol=len(input_files),
columnspacing=0.8,
)
loc="lower center",
fontsize=legend_size,
bbox_to_anchor=(0.5, -1.4),
fancybox=True,
shadow=False,
ncol=len(input_files),
columnspacing=0.8,
)
plt.tight_layout()
#axs[output_names.index(output_name)].get_ylim()[0])
axs[output_names.index(output_name)].set_ylim(axs[output_names.index(output_name)].get_ylim()[0]*0.925,axs[output_names.index(output_name)].get_ylim()[1]*1.075)
else:
# axs[output_names.index(output_name)].get_ylim()[0])
axs[output_names.index(output_name)].set_ylim(
axs[output_names.index(output_name)].get_ylim()[0] * 0.6,
axs[output_names.index(output_name)].get_ylim()[1] * 1.2,
)
else:
plt.grid(True)
plt.ylabel(
labels[output_name],
Expand Down Expand Up @@ -735,19 +733,21 @@ def main(args=None):
+ f"_vs_{output_name2}"
if output_names2 != []
else f"{args.outputdir}/scan_{scan_var_name}_vs_{output_names}"
+ f".{save_format}"
+ f".{save_format}",
dpi=300,
)
else:

else:
plt.savefig(
f"{args.outputdir}/scan_{scan_var_name}_vs_{output_name}"
+ f"_vs_{output_name2}"
if output_names2 != []
else f"{args.outputdir}/scan_{scan_var_name}_vs_{output_name}"
+ f".{save_format}"
+ f".{save_format}",
dpi=300,
)

if not stack_plots:# Display plot (used in Jupyter notebooks)
if not stack_plots: # Display plot (used in Jupyter notebooks)
plt.show()
plt.clf()
# ------------
Expand All @@ -761,18 +761,21 @@ def main(args=None):
# Number of scan points
n_scan_1 = int(m_file.data["isweep"].get_scan(-1))
n_scan_2 = int(m_file.data["isweep_2"].get_scan(-1))

# Selecting the converged runs only
contour_conv_ij = [] #List of non-converged scan point numbers
conv_ij = list() # 2D array of converged scan point numbers (sweep = rows, sweep_2 = columns)
contour_conv_ij = [] # List of non-converged scan point numbers
conv_ij = (
list()
) # 2D array of converged scan point numbers (sweep = rows, sweep_2 = columns)
ii_jj = 0
for ii in range(n_scan_1):
conv_ij.append(list())
for jj in range(n_scan_2):
ii_jj += 1 #Represents the scan point number in the MFILE
ii_jj += 1 # Represents the scan point number in the MFILE
ifail = m_file.data["ifail"].get_scan(ii_jj)
if ifail == 1:
conv_ij[ii].append(ii_jj) # Only appends scan number if scan converged
conv_ij[ii].append(
ii_jj
) # Only appends scan number if scan converged
contour_conv_ij.append(ii_jj)
else:
failed_value_1 = m_file.data[scan_var_name].get_scan(ii_jj)
Expand All @@ -786,9 +789,7 @@ def main(args=None):
for output_name in output_names:
# Check if the output variable exists in the MFILE
if output_name not in m_file.data.keys():
print(
f"Warning : `{output_name}` does not exist in PROCESS dicts"
)
print(f"Warning : `{output_name}` does not exist in PROCESS dicts")
print(f"Warning : `{output_name}` will not be output")
continue

Expand All @@ -807,37 +808,54 @@ def main(args=None):
output_contour_z = np.zeros((n_scan_1, n_scan_2))
x_contour = []
y_contour = []
for i in range(n_scan_2): #nscan2 = 13
x_contour.append(m_file.data[scan_2_var_name].get_scan(i+1))
for i in range(1,n_scan_1*n_scan_2,n_scan_2):
y_contour.append(m_file.data[scan_var_name].get_scan(i+1)) #is the separte lists in the list
for i in range(n_scan_2): # nscan2 = 13
x_contour.append(m_file.data[scan_2_var_name].get_scan(i + 1))
for i in range(1, n_scan_1 * n_scan_2, n_scan_2):
y_contour.append(
m_file.data[scan_var_name].get_scan(i + 1)
) # is the separte lists in the list
for i in contour_conv_ij:
# print(((i-1)%n_scan_2))
output_contour_z[((i-1)//n_scan_2)][((i-1)%n_scan_2) if ((i-1)//n_scan_2)%2==0 else (-((i-1)%n_scan_2)-1)] = m_file.data[output_name].get_scan(i)
#print(output_contour_z)

# if (x_contour[1]>x_contour[0]) and y_contour[1]>y_contour[0]
# print(((i-1)%n_scan_2))
output_contour_z[((i - 1) // n_scan_2)][
((i - 1) % n_scan_2)
if ((i - 1) // n_scan_2) % 2 == 0
else (-((i - 1) % n_scan_2) - 1)
] = m_file.data[output_name].get_scan(i)
# print(output_contour_z)

flat_output_z = output_contour_z.flatten()
flat_output_z.sort()

print(x_contour)
print(y_contour)
print(output_contour_z)
plt.contourf(
x_contour,
y_contour,
output_contour_z,
levels=np.linspace(flat_output_z[1], output_contour_z.max(), 50),
)
plt.colorbar(label =labels[output_name])
x_contour,
y_contour,
output_contour_z,
levels=np.linspace(
list(filter(lambda i: i > 0.0, flat_output_z))[0],
flat_output_z.max(),
50,
),
)
plt.colorbar(label=labels[output_name])
plt.ylabel(labels[scan_var_name], fontsize=axis_font_size)
plt.xlabel(labels[scan_2_var_name], fontsize=axis_font_size)
plt.tight_layout()
plt.savefig(
f"{args.outputdir}/scan_{output_name}_vs_{scan_var_name}_{scan_2_var_name}.{save_format}"
)
f"{args.outputdir}/scan_{output_name}_vs_{scan_var_name}_{scan_2_var_name}.{save_format}"
)
plt.show()
plt.clf()

else:
# Converged indexes, for normal 2D line plot
for conv_j in conv_ij: # conv_j is an array element containing the converged scan numbers
# Converged indexes, for normal 2D line plot
for (
conv_j
) in (
conv_ij
): # conv_j is an array element containing the converged scan numbers
# Scanned variables
print(conv_j)
scan_1_var_array = np.zeros(len(conv_j))
Expand Down

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