Skip to content

Fix/Tutorial-issues-with-imports #3

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
RedHeadBarak wants to merge 1 commit into
base: main
Choose a base branch
from
Open

Fix/Tutorial-issues-with-imports #3

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
104 changes: 79 additions & 25 deletions analysis/Tutorial/mibitof_tnbc_tutorial.ipynb
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -38,7 +38,9 @@
"FANMOD_path = \"C:\\\\Users\\\\User\\\\source\\\\repos\\\\fanmod-cmd\\\\out\\\\build\\\\x64-release\" #this should be updated\n",
"FANMOD_exe = \"LocalFANMOD.exe\"\n",
"output_dir = './../../fanmod_output'\n",
"cache_dir = './../../parse_cache'"
"cache_dir = './../../parse_cache'\n",
"\n",
"cism_project_root_path = 'C:\\\\Users\\\\milsh\\\\PycharmProjects\\\\CISM'"
]
},
{
Expand Down Expand Up @@ -366,6 +368,17 @@
"cell_type": "code",
"execution_count": 28,
"metadata": {},
"outputs": [],
"source": [
"# Changing directories so we can import CISM objects\n",
"import os\n",
"os.chdir(cism_project_root_path)"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"name": "stdout",
Expand Down Expand Up @@ -455,6 +468,17 @@
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [],
"source": [
"# Changing directories back to the tutorial\n",
"import os\n",
"os.chdir(cism_project_root_path + '\\\\analysis\\\\Tutorial')"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"data": {
Expand Down Expand Up @@ -626,6 +650,19 @@
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [],
"source": [
"# Changing directories so we can import CISM objects\n",
"import os\n",
"os.chdir(cism_project_root_path)"
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
Expand Down Expand Up @@ -692,6 +729,17 @@
"execution_count": 16,
"metadata": {},
"outputs": [],
"source": [
"# Changing directories back to the tutorial\n",
"import os\n",
"os.chdir(cism_project_root_path + '\\\\analysis\\\\Tutorial')"
]
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {},
"outputs": [],
"source": [
"from cism.cism import TissueStateDiscriminativeMotifs\n",
"from cism.cism import DiscriminativeFeatureKey\n",
Expand Down Expand Up @@ -842,6 +890,19 @@
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [],
"source": [
"# Changing directories so we can import CISM objects\n",
"import os\n",
"os.chdir(cism_project_root_path)"
]
},
{
"cell_type": "code",
"execution_count": 41,
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stdout",
Expand Down Expand Up @@ -997,7 +1058,7 @@
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "79f06f0e3c56465d9b565f27aa760f88",
"model_id": "9f247ecc9104465c8f4e078f3fa6a59d",
"version_major": 2,
"version_minor": 0
},
Expand All @@ -1011,7 +1072,7 @@
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "b1e9e84daefb4d8bbac3bb568ef140a7",
"model_id": "fa66119f47b5469999aad7a5e2eccc47",
"version_major": 2,
"version_minor": 0
},
Expand All @@ -1026,14 +1087,14 @@
"name": "stdout",
"output_type": "stream",
"text": [
"classes: ['Short-term survival', 'Long-term survival'] th:0.5 score: 0.7619047619047619\n",
"classes: ['Short-term survival', 'Long-term survival'] th:0.5 score: 0.7904761904761904\n",
"task: Short-term survival - Long-term survival\n"
]
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "e5027c40b5a34e979c8d7804c1089823",
"model_id": "60f5ce59c5c446a79139333619e59842",
"version_major": 2,
"version_minor": 0
},
Expand All @@ -1047,7 +1108,7 @@
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "77b56d9012c64959bbfed9f0120d3fda",
"model_id": "ee25cd9609364998b905531823ff7d43",
"version_major": 2,
"version_minor": 0
},
Expand All @@ -1069,7 +1130,7 @@
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "7aa321fa9891467db7e8aca07fa9f1c5",
"model_id": "f0cc6a4d2f4e4c998d1147266deb88f5",
"version_major": 2,
"version_minor": 0
},
Expand All @@ -1083,7 +1144,7 @@
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "42616a8bab164d57aa4fb4342d8bfb4e",
"model_id": "1154390e7243447492f7f80d84d9f259",
"version_major": 2,
"version_minor": 0
},
Expand All @@ -1105,7 +1166,7 @@
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "16a0144de57e4e23be03bebfaeca6eba",
"model_id": "e80cc956af2a4322bae07f8baf20add2",
"version_major": 2,
"version_minor": 0
},
Expand All @@ -1119,7 +1180,7 @@
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "06696fcdb7c84df29e98c5b98843397a",
"model_id": "ae706ef6a8434318935b6952c3d66b8d",
"version_major": 2,
"version_minor": 0
},
Expand All @@ -1134,14 +1195,14 @@
"name": "stdout",
"output_type": "stream",
"text": [
"classes: ['Short-term survival', 'Long-term survival'] th:0.75 score: 0.7380952380952381\n",
"classes: ['Short-term survival', 'Long-term survival'] th:0.75 score: 0.7333333333333334\n",
"task: Short-term survival - Long-term survival\n"
]
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "5276197cf2444f15977aac74c9728c7f",
"model_id": "8a31013922644920b08533175f4d6724",
"version_major": 2,
"version_minor": 0
},
Expand All @@ -1155,7 +1216,7 @@
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "17f464bce407409eb4811da28d6d5814",
"model_id": "b93dfe4866e24d28adc01772a883cf6d",
"version_major": 2,
"version_minor": 0
},
Expand Down Expand Up @@ -1238,13 +1299,13 @@
},
{
"cell_type": "code",
"execution_count": 21,
"execution_count": 42,
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "093dddf3f3c744b49bf60f72c50ee9e4",
"model_id": "0607e34541a44cbdb1e2578b42d882eb",
"version_major": 2,
"version_minor": 0
},
Expand Down Expand Up @@ -1277,14 +1338,14 @@
},
{
"cell_type": "code",
"execution_count": 22,
"execution_count": 43,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"we have 33 discriminative motifs\n"
"we have 31 discriminative motifs\n"
]
}
],
Expand All @@ -1301,7 +1362,7 @@
},
{
"cell_type": "code",
"execution_count": 23,
"execution_count": 44,
"metadata": {},
"outputs": [
{
Expand Down Expand Up @@ -2023,13 +2084,6 @@
" target_motif = helpers.string_base64_pickle(target_motif)\n",
" draw.draw_motif(target_motif, cells_type=cells_type)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
Expand Down